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Cancers, Volume 17, Issue 3 (February-1 2025) – 226 articles

Cover Story (view full-size image): The human papillomavirus (HPV) is a prevalent sexually transmitted infection known to cause numerous morbidities, which have increased significantly over two decades. This study investigated awareness and knowledge of HPV, oropharyngeal cancer (OPC), and the HPV vaccine. University students (n = 1005) answered questions related to their awareness and knowledge of HPV. The results indicate relatively high levels of awareness but significant gaps in their knowledge of HPV, OPC, and the HPV vaccine. These data suggest that such limitations may place younger adults at greater risk for HPV-related infections. The present data may guide future efforts directed toward better education on HPV. View this paper
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22 pages, 3136 KiB  
Article
GATA3-Driven ceRNA Network in Lung Adenocarcinoma Bone Metastasis Progression and Therapeutic Implications
by Yun Liu, Shihui Shen, Xudong Wang, Hansen Chen, Wenjie Ren, Haifeng Wei, Kun Li and Lei Li
Cancers 2025, 17(3), 559; https://doi.org/10.3390/cancers17030559 - 6 Feb 2025
Viewed by 651
Abstract
Background/Objectives: Bone metastasis is a common and severe complication of lung adenocarcinoma (LUAD), impacting prognosis and treatment outcomes. Understanding the molecular mechanisms behind LUAD bone metastasis (LUADBM) is essential for developing new therapeutic strategies. The interactions between long non-coding RNAs (lncRNAs), microRNAs [...] Read more.
Background/Objectives: Bone metastasis is a common and severe complication of lung adenocarcinoma (LUAD), impacting prognosis and treatment outcomes. Understanding the molecular mechanisms behind LUAD bone metastasis (LUADBM) is essential for developing new therapeutic strategies. The interactions between long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in the competing endogenous RNA (ceRNA) network are crucial in cancer progression and metastasis, but the regulatory mechanisms in LUADBM remain unclear. Methods: Microarray analysis was performed on clinical samples, followed by weighted gene co-expression network analysis (WGCNA) and construction of a ceRNA network. Molecular mechanisms were validated using colony formation assays, transwell migration assays, wound healing assays to assess cell migration, and osteoclastogenesis assays to evaluate osteoclast differentiation. Potential therapeutic drugs and their binding affinities were predicted using the CMap database and Kdeep. The interaction between the small-molecule drug and its target protein was confirmed by surface plasmon resonance (SPR) and drug affinity responsive target stability (DARTS) assays. Mechanistic insights and therapeutic efficacy were further validated using patient-derived organoid (PDO) cultures, drug sensitivity assays, and in vivo drug treatments. Results: Our results identified the XLOC_006941/hsa-miR-543/NPRL3 axis as a key regulatory pathway in LUADBM. We also demonstrated that GATA3-driven Th2 cell infiltration creates an immunosuppressive microenvironment that promotes metastasis. Additionally, we confirmed that the inhibitor E7449 effectively targets NPRL3, and its combination with the IL4R-blocking antibody dupilumab resulted in improved therapeutic outcomes in LUADBM. Conclusions: These findings offer new insights into the molecular mechanisms of LUADBM and highlight potential therapeutic targets, including the XLOC_006941/miR-543/NPRL3 axis and GATA3-driven Th2 cell infiltration. The dual-target therapy combining E7449 with dupilumab shows promise for improving patient outcomes in LUADBM, warranting further clinical evaluation. Full article
(This article belongs to the Special Issue Bone and Spine Metastases)
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<p>lncRNA XLOC_006941 promotes LUADBM initiation and metastasis via a novel ceRNA network. (<b>A</b>) Heatmap showing lncRNA and mRNA expression categorization into modules and their correlations with clinical traits; (<b>B</b>) Sankey diagram illustrating the ceRNA network and potential molecule interactions; (<b>C</b>) RT-qPCR quantification of five lncRNAs in the ceRNA network between A549L0 and A549L6 cells; (<b>D</b>) Colony formation assay (left) and bar graph (right) depicting colony numbers in control and XLOC_006941 knockdown cell lines; (<b>E</b>) Transwell assay images (left) and bar graph (right) showing migration differences in control and XLOC_006941 knockdown cells. Scale bar, 200 µm; (<b>F</b>) Osteoclastogenesis ability in BMMs between control and XLOC_006941 knockdown cells (left, images; right, bar graph). Scale bar, 200 µm; (<b>G</b>) Bioluminescence (BLI, left) and μCT (right) images showing the effect of XLOC_006941 knockdown in a mouse model of bone metastasis, with red arrows indicating bone destruction. Scale bar, 1 mm; (<b>H</b>) Weekly quantification of BLI intensity in mice receiving shXLOC_006941 or control H441 cells. Data shown represent mean ± s.e.m. (<span class="html-italic">n</span> = 3). ns, not statistically significant, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">p</span> values were analyzed by an unpaired, two-tailed <span class="html-italic">t</span>-test or one-way ANOVA multiple comparisons test.</p>
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<p>hsa-miR-543 and NPRL3 as downstream molecules regulated by XLOC_006941 function in the progression of LUADBM. (<b>A</b>) Normalized hsa-miR-543 expression in LUAD and LUADBM microarray data; (<b>B</b>) Colony formation images (left) and statistical analysis (right) comparing hsa-miR-543 overexpression (OE) cells to controls; (<b>C</b>) Transwell assay images (left) and bar graph (right) of control and hsa-miR-543 overexpression cells. Scale bar, 200 µm; (<b>D</b>) BLI showing the effect of AAV negative control (NC) and AAV hsa-miR-543 in a LUADBM mouse model induced by H441 left ventricular injection; (<b>E</b>) Weekly variation in AAV hsa-miR-543 treatment compared to AAV NC via tail vein injection in a LUADBM mouse model induced by H441 left ventricular injection; (<b>F</b>) Normalized NPRL3 expression in normal, LUAD, and LUADBM tissues; (<b>G</b>) Relative NPRL3 RNA expression in BEAS-2B, A549L0, and A549L6 cells; (<b>H</b>) NPRL3 protein expression in BEAS-2B, A549L0, and A549L6 cells; (<b>I</b>) Colony formation ratios comparing NPRL3 overexpression cells to controls; (<b>J</b>) Transwell assay images (left) and bar graph (right) of control and NPRL3 overexpression cells. Scale bar, 200 µm. Data shown represent mean ± s.e.m. (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">p</span> values were analyzed by the unpaired, two-tailed <span class="html-italic">t</span>-test or one-way ANOVA multiple comparisons test.</p>
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<p>XLOC_006941 sponges hsa-miR-543 to rescue NPRL3, forming a ceRNA network that regulates LUADBM progression. (<b>A</b>) Expression correlation between XLOC_006941 and NPRL3 in LUADBM microarray data; (<b>B</b>) Relative luciferase activity displays the interaction between XLOC_006941 WT/Mut or NPRL3 3′UTR WT/Mut and hsa-miR-543. WT, wild type; Mut, mutant; (<b>C</b>) Relative expression in XLOC_006941 knockdown and double knockdown of XLOC_006941, hsa-miR-543 cells; (<b>D</b>) Representative images of colony formation in XLOC_006941 knockdown and XLOC_006941, hsa-miR-543 double knockdown cells; (<b>E</b>) S Statistical analysis of colony formation in XLOC_006941 knockdown and double knockdown cells; (<b>F</b>) Wound healing assay results after 24 h; (<b>G</b>) BMM osteoclastogenesis assay results after 7 days, with representative images (left) and statistical analysis (right). Scale bar, 200 µm. Data shown represent mean ± s.e.m. (<span class="html-italic">n</span> = 3). ns, not statistically significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">p</span> values were analyzed by the unpaired, two-tailed <span class="html-italic">t</span>-test or one-way ANOVA multiple comparisons test.</p>
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<p>GATA3 functions as a transcription factor of the ceRNA network in LUADBM. (<b>A</b>) Venn diagram illustrating the number of transcription factors potentially binding to motifs within five lncRNAs, analyzed using the JASPAR database; (<b>B</b>) Normalized GATA3 expression in microarray data from normal, LUAD, and LUADBM tissues; (<b>C</b>) Relative RNA expression of GATA3 in A549L0 and A549L6 cells compared to BEAS-2B cells; (<b>D</b>) Protein expression of GATA3 in BEAS-2B, A549L0, and A549L6 cells; (<b>E</b>) Relative XLOC_006941 expression in GATA3 knockdown cells compared to control cells; (<b>F</b>) Relative luciferase activity of XLOC_006941 promoter reporter in A549L6 cells with or without GATA3 overexpression; (<b>G</b>) Relative luciferase activity of XLOC_006941 promoter reporter in A549L6 cells with or without GATA3 knockdown. Data shown represent mean ± s.e.m. (<span class="html-italic">n</span> = 3). ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">p</span> values were analyzed by the unpaired, two-tailed <span class="html-italic">t</span>-test or one-way ANOVA multiple comparisons test.</p>
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<p>Increased Th2 cell infiltration and a GATA3/RP11-508N12.2/hsa-miR-136-5p/IL4R ceRNA axis contribute to LUADBM progression. (<b>A</b>) Immune cell abundance in LUADBM; (<b>B</b>) Representative flow cytometry plots of Th2 cells within T cells in normal, LUAD, and LUADBM tissues; (<b>C</b>) Percentages of Th2 cells within T cells in normal, LUAD, and LUADBM tissues; (<b>D</b>) GSVA analysis of the 7 mRNAs in the ceRNA network using the immune dataset; (<b>E</b>) Normalized IL4R expression in LUAD and LUADBM tissues; (<b>F</b>) IL4R RNA expression in BEAS-2B, A549L0, and A549L6 cells; (<b>G</b>) IL4R protein expression in BEAS-2B, A549L0, and A549L6 cells; (<b>H</b>) Protein expression following 200 ng/mL IL4 treatment for 30 min in A549L6 cells; (<b>I</b>) Correlation between RP11-508N12.2 and IL4R in LUADBM microarray data; (<b>J</b>) Normalized expression of hsa-miR-136-5p in LUAD and LUADBM tissues; (<b>K</b>) R Luciferase activity showing interaction between RP11-508N12.2 WT/Mut or IL4R 3′UTR WT/Mut and hsa-miR-136-5p. WT, wild type; Mut, mutant. Data shown represent mean ± s.e.m. (<span class="html-italic">n</span> = 3). ns, not statistically significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">p</span> values were analyzed by the unpaired, two-tailed <span class="html-italic">t</span>-test or one-way ANOVA multiple comparisons test.</p>
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<p>Targeting the ceRNA network offers promising therapeutic strategies for LUADBM. (<b>A</b>) The top five small molecule drugs predicted by the CMap database to potentially reverse gene expression in LUADBM; (<b>B</b>) IC<sub>50</sub> values of small molecules E7449, K-02288, and Rhapontin in A549L6 cells; (<b>C</b>) IC<sub>50</sub> values of E7449 in BEAS-2B, A549L0, and A549L6 cells; (<b>D</b>) NPRL3 expression in DARTs assay following treatments with DMSO, 10 µM E7449, or 30 µM E7449; (<b>E</b>) SPR sensorgrams showing the binding of E7449 to immobilized NPRL3; (<b>F</b>) IC<sub>50</sub> values of E7449 in control and NPRL3 knockdown A549L6 cells; (<b>G</b>) Docking model of E7449 with NPRL3 N-terminal longin domain; (<b>H</b>) A549L6 cell viability following treatment with 1/2 IC<sub>50</sub> or IC<sub>50</sub> concentration of E7449 over 96 h; (<b>I</b>) Representative images (left) and statistical bar plot (right) comparing the migration of control cells and E7449-treated cells by the transwell assay. Scale bar, 200 µm; (<b>J</b>) BLI image (left) and µCT (right) showing the effect of 40 mg/kg E7449 in a mouse model of LUADBM induced by H441 left ventricular injection. Red arrows in the μCT image highlight the regions of bone destruction. Scale bar, 1 mm; (<b>K</b>) Representative fluorescent images of LUADBM PDO treated with 5 µM E7449; (<b>L</b>) Statistic bar plot of LUADBM PDO treated with 5 µM E7449; (<b>M</b>) Cell viability after treatment with varying concentrations of dupilumab, followed by a 30-min induction with 200 ng/mL IL4; (<b>N</b>) Representative fluorescent images of LUADBM PDO treated with 150 µg/mL dupilumab or a combination of E7449 and dupilumab (left) and corresponding bar plot (right). Scale bar, 200 µm. Data shown represent mean ± s.e.m. (<span class="html-italic">n</span> = 3). ns, not statistically significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">p</span> values were analyzed by the unpaired, two-tailed <span class="html-italic">t</span>-test or one-way ANOVA multiple comparisons test.</p>
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23 pages, 736 KiB  
Systematic Review
Applications of Artificial Intelligence for Metastatic Gastrointestinal Cancer: A Systematic Literature Review
by Amin Naemi, Ashkan Tashk, Amir Sorayaie Azar, Tahereh Samimi, Ghanbar Tavassoli, Anita Bagherzadeh Mohasefi, Elaheh Nasiri Khanshan, Mehrdad Heshmat Najafabad, Vafa Tarighi, Uffe Kock Wiil, Jamshid Bagherzadeh Mohasefi, Habibollah Pirnejad and Zahra Niazkhani
Cancers 2025, 17(3), 558; https://doi.org/10.3390/cancers17030558 - 6 Feb 2025
Viewed by 634
Abstract
Background/Objectives: This systematic literature review examines the application of Artificial Intelligence (AI) in the diagnosis, treatment, and follow-up of metastatic gastrointestinal cancers. Methods: The databases PubMed, Scopus, Embase (Ovid), and Google Scholar were searched for published articles in English from January 2010 to [...] Read more.
Background/Objectives: This systematic literature review examines the application of Artificial Intelligence (AI) in the diagnosis, treatment, and follow-up of metastatic gastrointestinal cancers. Methods: The databases PubMed, Scopus, Embase (Ovid), and Google Scholar were searched for published articles in English from January 2010 to January 2022, focusing on AI models in metastatic gastrointestinal cancers. Results: forty-six studies were included in the final set of reviewed papers. The critical appraisal and data extraction followed the checklist for systematic reviews of prediction modeling studies. The risk of bias in the included papers was assessed using the prediction risk of bias assessment tool. Conclusions: AI techniques, including machine learning and deep learning models, have shown promise in improving diagnostic accuracy, predicting treatment outcomes, and identifying prognostic biomarkers. Despite these advancements, challenges persist, such as reliance on retrospective data, variability in imaging protocols, small sample sizes, and data preprocessing and model interpretability issues. These challenges limit the generalizability, clinical application, and integration of AI models. Full article
(This article belongs to the Section Systematic Review or Meta-Analysis in Cancer Research)
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<p>Flow diagram of study selection (PRISMA chart).</p>
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16 pages, 472 KiB  
Review
BTK Is the Target That Keeps on Giving: A Review of BTK-Degrader Drug Development, Clinical Data, and Future Directions in CLL
by Ross T. Salvaris, Jamie Brennan and Katharine L. Lewis
Cancers 2025, 17(3), 557; https://doi.org/10.3390/cancers17030557 - 6 Feb 2025
Viewed by 793
Abstract
Effective available treatment options for patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) who relapse after becoming refractory to both a covalent Bruton Tyrosine Kinase inhibitor (cBTKi) and a B cell leukemia/lymphoma 2 inhibitor (BCL2i) remain limited, and prognosis is very poor. Emerging [...] Read more.
Effective available treatment options for patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) who relapse after becoming refractory to both a covalent Bruton Tyrosine Kinase inhibitor (cBTKi) and a B cell leukemia/lymphoma 2 inhibitor (BCL2i) remain limited, and prognosis is very poor. Emerging areas of drug development include cellular therapies such as chimeric antigen receptor T-cell therapy and bispecific antibodies. However, cost, accessibility, toxicity, and the need for either prolonged or repeated hospitalization prevent universal application of these therapies. Given this area of unmet clinical need, we present this review article on Bruton Tyrosine Kinase (BTK) degraders in patients with CLL/SLL. We focus on their development as a drug class, the up-to-date clinical data available, as well as future directions. BTK protein degraders are a novel drug class with an alternate mechanism of action (MOA), compared to cBTKis and non-covalent BTKis (ncBTKis), causing ubiquitination of BTK, thereby leading to its degradation through the proteasome. Encouraging pre-clinical data show that this MOA allows BTK protein degraders to overcome common BTK mutations. We focus on four agents which are under investigation in B-cell malignancies in early clinical trials: BGB-16673, NX-2127, NX-5948, and AC676. Preliminary data suggest a comparable safety and toxicity profile between agents across this drug class with many patients on phase 1 trials deriving durable clinical benefit. Optimal sequencing of BTK degraders in the therapeutic landscape of CLL/SLL treatment is yet to be established. Further trials investigating these agents in combination with other targeted CLL agents may help to further understand their applicability. An effective, tolerable oral class of drugs would be invaluable in the treatment of patients with multiply relapsed CLL/SLL. Full article
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<p><b>BTK degrader mechanism of action.</b> Bruton tyrosine kinase (BTK) degraders cause degradation of the BTK protein through the ubiquitin–proteasome system. <b>1</b>, Degraders consist of three components: a ligand that binds to BTK (“BTK hook”) and a ligand that binds an E3 ligase (e.g., cereblon). <b>2</b>, When the degrader binds to BTK, thereby forming a tertiary complex, it leads to ubiquitination. <b>3</b>, Ubiquitination of BTK leads to its degradation by the proteasome.</p>
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8 pages, 1737 KiB  
Communication
T-Cell Receptor Rearrangements in Early Stages of Mycosis Fungoides May Be Associated with Pronounced Copy Number Variations: A Prognostic Factor?
by Carsten Hain, Cassandra Cieslak, Jörn Kalinowski and Rudolf Stadler
Cancers 2025, 17(3), 556; https://doi.org/10.3390/cancers17030556 - 6 Feb 2025
Viewed by 480
Abstract
Mycosis fungoides (MF), the most common form of cutaneous T-cell lymphoma, poses significant diagnostic challenges due to its overlap with benign inflammatory skin diseases and the absence of specific symptoms. Accurate early diagnosis and stratification of patients by progression risk are essential for [...] Read more.
Mycosis fungoides (MF), the most common form of cutaneous T-cell lymphoma, poses significant diagnostic challenges due to its overlap with benign inflammatory skin diseases and the absence of specific symptoms. Accurate early diagnosis and stratification of patients by progression risk are essential for effective treatment. This study proposes a proof-of-concept for integrating T-cell receptor (TCR) clonality analysis with somatic mutation profiling to enhance diagnostic confidence and prognostic accuracy in early-stage MF. This study’s methodology comprised the analysis of nine patients with early MF (stages IA/IB) using whole-exome sequencing and TCR repertoire profiling. The analysis revealed the presence of clonal TCR rearrangements in seven patients, while somatic mutations were identified in two. A notable finding was a recurrent chromosome 7 trisomy in these two cases. The patients were stratified into three molecular profiles: (1) somatic mutations with clonal TCR rearrangement (n = 2), (2) clonal TCR rearrangement without somatic mutations (n = 4), and (3) neither somatic mutations nor clonal TCR rearrangement (n = 3). These findings emphasise the heterogeneity of MF and underscore the limitations of relying solely on TCR clonality or mutation burden for diagnosis. This study underscores the potential of somatic mutations as diagnostic markers to distinguish MF from benign conditions and as prognostic indicators for disease progression. A combined genetic approach may refine treatment decisions, particularly for patients with higher tumor cell fractions and pronounced genetic alterations. Despite the limited size of the cohort, the results advocate for larger, multi-center studies to validate these findings and integrate genetic analyses into routine MF management. Full article
(This article belongs to the Special Issue Oncogenesis of Lymphoma)
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<p>Histological and macroscopic pictures of exemplary patients. Patient 8 presents with a well-circumscribed patch at the lower right back. Histology shows subepidermal bandlike, slightly epidermotropic lymphocytes with a CD4 phenotype. Patient 7 shows disseminated patches on the upper back and arm with a subepidermal dense epidermotropic infiltrate of small lymphocytes with a CD4 phenotype. HE: hematoxylin–eosin staining.</p>
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<p>Genetic data of nine early-stage MF patients. For each patient, the copy number landscape, the number of SNVs, and the distribution of T-cell receptor alleles for the gamma (TRG) and beta (TRB) gene is shown. Positive values in the CNV plot indicate amplification, while negative values indicate deletions. Clear CNVs are only visible in samples 3 and 7, best indicated by the chr7 amplification present in both samples. This correlates with the number of SNVs, which is above potential background noise in samples 3 and 7. The T-cell receptor repertoire is depicted as a stacked bar of individual allele frequencies (grey bars). The alleles used for TCF calculation are marked in blue and orange (TRG) and blue (TRB).</p>
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21 pages, 572 KiB  
Review
Biomarkers for the Evaluation of Immunotherapy in Patients with Cholangiocarcinoma
by Thaleia-Eleftheria Bousou, Panagiotis Sarantis, Ioanna A. Anastasiou, Eleni-Myrto Trifylli, Dimitris Liapopoulos, Dimitra Korakaki, Evangelos Koustas, Michalis Katsimpoulas and Michalis V. Karamouzis
Cancers 2025, 17(3), 555; https://doi.org/10.3390/cancers17030555 - 6 Feb 2025
Viewed by 625
Abstract
Cholangiocarcinoma is a rare primary liver cancer with poor prognosis, due to the advanced stage at the time of diagnosis and limited therapeutic options, with poor response. Chemotherapy remains the standard first-line treatment, but the advent of immunotherapy has recently induced promising results. [...] Read more.
Cholangiocarcinoma is a rare primary liver cancer with poor prognosis, due to the advanced stage at the time of diagnosis and limited therapeutic options, with poor response. Chemotherapy remains the standard first-line treatment, but the advent of immunotherapy has recently induced promising results. Given the fact that diagnosis frequency is increasing nowadays and the survival rate remains very low, it is crucial to recognize patients who are suitable for immunotherapy and will have the best response. Different types of biomarkers, such as interleukins, exosomes, mi-RNA, ctDNA, and gene mutations, have been studied for their feasibility, not only for the early diagnosis of biliary tract cancer but also for the determination of responsiveness in treatment. Less frequently, these studies focus on finding and observing biomarkers in patients who receive immunotherapy. This review aims to summarize current knowledge of existing/promising biomarkers in patients with unresectable or metastatic cholangiocarcinoma, treated with immunotherapy as monotherapy, or combined with chemotherapy. Full article
(This article belongs to the Special Issue Developments in the Management of Gastrointestinal Malignancies)
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<p>Predictive biomarkers for patients taking ICIs for CCA. (Created in BioRender.com). * not-mutated version based on Xiaofeng Chen et al. study of 11 key mutated genes (e.g., APC, ARID1A, ERBB2, LRP1B, TNFAIP3).</p>
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15 pages, 4721 KiB  
Article
Salivary Gland Volume Changes and Dry Mouth Symptom Following Definitive Radiation Therapy in Oropharyngeal Cancer Patients—A Comparison of Two Different Approaches: Intensity-Modulated Radiation Therapy Versus Intensity-Modulated Radiation Therapy/Intensity-Modulated Proton Therapy Combination
by Seung Gyu Park, Yong Chan Ahn, Dongryul Oh, Kyungmi Yang, Sang Gyu Ju, Jin Man Kim, Dongyeol Kwon, Euncheol Choi and Han Gyul Yoon
Cancers 2025, 17(3), 554; https://doi.org/10.3390/cancers17030554 - 6 Feb 2025
Viewed by 795
Abstract
Background/Objectives: We aimed to compare the salivary gland volume changes following intensity-modulated radiation therapy (IMRT) alone versus IMRT/intensity-modulated proton therapy (IMPT) combination in oropharyngeal cancer (OPC). Methods: We retrospectively reviewed 78 OPC patients who underwent definitive RT with ipsilateral neck irradiation. [...] Read more.
Background/Objectives: We aimed to compare the salivary gland volume changes following intensity-modulated radiation therapy (IMRT) alone versus IMRT/intensity-modulated proton therapy (IMPT) combination in oropharyngeal cancer (OPC). Methods: We retrospectively reviewed 78 OPC patients who underwent definitive RT with ipsilateral neck irradiation. RT techniques were either IMRT alone or IMRT/IMPT combination. Salivary gland volumes over time in relation to dry mouth symptom were evaluated. Results: Patients’ characteristics were well balanced between groups. The mean dose to the ipsilateral parotid gland (PG) was significantly lower in IMRT alone than in IMRT/IMPT combination, while those to the contralateral PG and submandibular glands (SMGs) were significantly higher in IMRT alone. The volume ratio of ipsilateral PG showed an initial sharp decline, reaching 0.74, and stabilized thereafter. The ipsilateral SMG showed a continuous decline until 24 months and reached approximately 0.47 by 48 months. The contralateral PG/SMG showed initial decline and subsequent recovery to the initial volume by 48 months. There were no significant differences in salivary gland volume changes between groups. Within 6 months, 60.3% of patients experienced dry mouth symptom, and the dry mouth incidence decreased to 41.0% in 12 months and remained stable thereafter. There were no significant differences in dry mouth symptom between groups. The volume reduction in the ipsilateral salivary glands was greater in patients with dry mouth symptom. Conclusions: No significant differences in salivary gland volume changes and dry mouth symptom were apparent between groups. The critical factor in salivary gland volume change was the delivered dose to the salivary glands, not the RT techniques. Full article
(This article belongs to the Special Issue Clinical and Translational Research in Head and Neck Cancer)
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<p>Changes in salivary gland volume ratio over time (post-RT volume/initial volume). Note: All months indicate the number of months after the end of treatment. Statistically significant intervals are noted with red lines.</p>
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<p>Changes in salivary gland volume ratio over time (post-RT volume/initial volume) according to the treatment groups. Note: All months indicate the number of months after the end of treatment.</p>
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<p>Changes in salivary gland volume ratio over time (post-RT volume/initial volume) according to the presence of dry mouth symptom. Note: All months indicate the number of months after the end of treatment.</p>
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16 pages, 2388 KiB  
Article
Untargeted Metabolomics and Liquid Biopsy Investigation of Circulating Biomarkers in Soft Tissue Sarcoma
by Daniela Grasso, Barbara Marzocchi, Guido Scoccianti, Ilaria Palchetti, Domenico Andrea Campanacci, Lorenzo Antonuzzo, Federico Scolari, Serena Pillozzi and Andrea Bernini
Cancers 2025, 17(3), 553; https://doi.org/10.3390/cancers17030553 - 6 Feb 2025
Viewed by 561
Abstract
Background: Soft tissue sarcomas (STSs) are rare, highly malignant mesenchymal tumours, comprising approximately 1% of all adult cancers and about 15% of paediatric solid tumours. STSs exhibit considerable genomic complexity with diverse subtypes, posing significant clinical challenges. Objectives: This study aims to characterise [...] Read more.
Background: Soft tissue sarcomas (STSs) are rare, highly malignant mesenchymal tumours, comprising approximately 1% of all adult cancers and about 15% of paediatric solid tumours. STSs exhibit considerable genomic complexity with diverse subtypes, posing significant clinical challenges. Objectives: This study aims to characterise the molecular signature of primary STS through liquid biopsies and the untargeted metabolomic profiling of 75 patients, providing deep insights into cellular processes and potential therapeutic targets. Methods: This study analysed serum samples using nuclear magnetic resonance (NMR) spectroscopy for metabolomic profiling. Multivariate data analysis and machine learning classifiers were employed to identify biomarkers. Results: A panel of eleven significant deregulated metabolites were discovered in serum samples of patients with STS, with potential implications for cancer diagnosis and treatment. Conclusions: Choline decrease emerged as a marker for cancer progression, highlighting the potential of targeting its metabolism for therapeutic approaches in STS. The NMR analysis protocol proved effective for determining circulating biomarkers from liquid biopsies, making it suitable for rare disease research. Full article
(This article belongs to the Special Issue New Biomarkers in Cancers 2nd Edition)
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<p>Hydrogen 1D spectrum (aliphatic region) of serum sample from an STS patient. Signals of some relevant metabolites among the sixty-two identified are labelled. The lower limit of detection (LoD) was estimated to be 1 µM.</p>
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<p>PCA (<b>a</b>) and PLS-DA (<b>b</b>) scores plot of patients with STS (red) vs. healthy controls (green). Intra-group variation in patients is broad compared to the minimal variation in controls.</p>
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<p>(<b>a</b>) Plot of OOB error for RF classification of the two groups; overall OOB estimate is 0.04. (<b>b</b>) Mean decrease in accuracy indicates the features most relevant to the model; red and blue squares indicate higher and lower concentrations, respectively.</p>
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<p>Acetoacetate (AcAc), provided by 3-hydroxybutyrate (3HB) dehydrogenation by 3-hydroxybutyrate dehydrogenase (3HBD), can be either converted to acetone through non-enzymatic decarboxylation or to acetyl-CoA. Indeed, AcAc is first converted by succinyl-CoA:3-ketoacid CoA transferase (SCOT) to acetoacetyl-CoA (AcAc-CoA), the substrate of acetoacetyl-CoA thiolase (ACAT). Acetyl-CoA goes through the citric acid cycle and, after oxidative phosphorylation, produces 12 ATP per molecule. Acetone is not re-converted to acetyl-CoA, which is either excreted through urine or exhaled.</p>
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<p>Purine salvage pathway. In healthy people, inosine is usually degraded into uric acid and excreted in urine. However, in STS, there are high concentrations of inosine and hypoxanthine, suggesting tumour cells are not capable of de novo synthesis due to their hypoxic state and salvage can be exploited. Inosine and hypoxanthine are then re-converted into purine nucleotides.</p>
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<p>(<b>a</b>) Purines’ aromatic ring region of the NMR spectrum from an STS serum (black) shows the typical signals of inosine (Ino) (29 µM) and hypoxanthine (Hyp) (25 µM); such signals are absent in all control spectra (red) down to the lower limit of detection (1 µM). Satellite peaks from formate arise in this area due to residual 13C coupling and are to be ignored. (<b>b</b>) Simulated peaks from purine rings: adenosine (Ado), adenine (Ade), xanthine (Xan), inosine (Ino), hypoxanthine (Hyp), and adenosine nucleotides (AMP, ADP, ATP). Large peak dispersion in such spectral region (7.8–8.4 ppm) is apparent, making purines effectively identifiable and quantifiable by NMR. Patients show remarkable Ino and Hyp levels (blue) but not the other purines (pink).</p>
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<p>Comparison of peak area, proportional to concentration, of lactate alpha-hydrogen signal between representative patient (black, C = 2.3 mM) and control (red, C = 1.1 mM). The large excess of lactate in the patient is apparent.</p>
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17 pages, 2930 KiB  
Article
Predictors of the Development of Gastric Cancer in Post-Helicobacter pylori-Eradication Patients Followed Up for More than 10 Years: A Histological, Serological, and Endoscopic Study
by Kazuhiro Mizukami, Masaaki Kodama, Yuka Hirashita, Masahide Fukuda, Sotaro Ozaka, Koshiro Tsutsumi, Ryota Sagami, Kensuke Fukuda, Ryo Ogawa and Kazunari Murakami
Cancers 2025, 17(3), 552; https://doi.org/10.3390/cancers17030552 - 6 Feb 2025
Viewed by 726
Abstract
Background/Objectives: Although Helicobacter pylori (H. pylori) eradication therapy is important for preventing gastric cancer (GC), the occurrence of GC after H. pylori eradication remains a problem. In this study, the aim was to identify risk factors for GC after H. pylori [...] Read more.
Background/Objectives: Although Helicobacter pylori (H. pylori) eradication therapy is important for preventing gastric cancer (GC), the occurrence of GC after H. pylori eradication remains a problem. In this study, the aim was to identify risk factors for GC after H. pylori eradication by comparing long-term histological, endoscopic, and serological evaluations of patients with and without GC. Methods: Patients who underwent H. pylori eradication therapy at Oita University Hospital between June 1997 and August 2013 and were followed for at least 3 years with long-term endoscopy, histology, and serum biochemical tests were included, and the GC (215 cases) and non-GC (11 cases) groups were compared. Results: The GC group was older than the non-GC group at the time of eradication, had lower serum pepsinogen I/II levels, had severe endoscopic atrophic changes, had higher activity at the antrum, and inflammation and intestinal metaplasia (IM) at the corpus on updated Sydney system scoring. On long-term follow-up after eradication, the GC group had a wider range of endoscopic mucosal atrophy and a lower serum pepsinogen I/II ratio at any time point. Conclusions: Endoscopic mucosal atrophy and the serum pepsinogen I/II ratio are useful predictors of GC in patients post H. pylori eradication at any time point. Full article
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<p>Flow chart of study design.</p>
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<p>Comparison of updated Sydney system score at the antrum between GC and non-GC group. (<b>a</b>) Inflammation at the antrum. (<b>b</b>) Atrophy at the antrum. (<b>c</b>) IM at the antrum. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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<p>Comparison of updated Sydney system score at the antrum between GC and non-GC group. (<b>a</b>) Inflammation at the antrum. (<b>b</b>) Atrophy at the antrum. (<b>c</b>) IM at the antrum. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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<p>Comparison of updated Sydney system score at the corpus between GC and non-GC group. (<b>a</b>) Inflammation at the corpus. (<b>b</b>) Atrophy at the corpus. (<b>c</b>) IM at the corpus. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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<p>Comparison of updated Sydney system score at the corpus between GC and non-GC group. (<b>a</b>) Inflammation at the corpus. (<b>b</b>) Atrophy at the corpus. (<b>c</b>) IM at the corpus. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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<p>Comparison of endoscopic atrophy score between GC and non-GC group. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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<p>Comparison of serum pepsinogen titer between GC and non-GC group. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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<p>Comparison of serum pepsinogen titer between GC and non-GC group. Periods after eradications were defined as follows: 1, before eradication; 2, 10–14 months after eradication; 3, 15–42 months after eradication; 4, 43–109 months after eradication; 5, more than 110 months after eradication. <span class="html-italic">p</span>-values were calculated by Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05, GC vs. non-GC group.</p>
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12 pages, 1342 KiB  
Article
Periostin from Tumor Stromal Cells Might Be Associated with Malignant Progression of Colorectal Cancer via Smad2/3
by Canfeng Fan, Qiang Wang, Saki Kanei, Kyoka Kawabata, Hinano Nishikubo, Rika Aoyama, Zhonglin Zhu, Daiki Imanishi, Takashi Sakuma, Koji Maruo, Gen Tsujio, Yurie Yamamoto, Tatsunari Fukuoka and Masakazu Yashiro
Cancers 2025, 17(3), 551; https://doi.org/10.3390/cancers17030551 - 6 Feb 2025
Viewed by 547
Abstract
Background/Objectives: Cancer-associated fibroblasts (CAFs) in the tumor microenvironment have been reported to be closely associated with tumor progression in various types of cancer, including colorectal cancer (CRC). Periostin, a matricellular protein, was reported to be expressed on both cancer cells and surrounding tumor [...] Read more.
Background/Objectives: Cancer-associated fibroblasts (CAFs) in the tumor microenvironment have been reported to be closely associated with tumor progression in various types of cancer, including colorectal cancer (CRC). Periostin, a matricellular protein, was reported to be expressed on both cancer cells and surrounding tumor stromal cells, such as CAFs, and is regulated by Smad2/3 signaling. In this study, we aimed to clarify the clinicopathologic significance of periostin and Smad2/3 expression in CRC, with a particular focus on the tumor microenvironment. Methods: A total of 351 CRC patients were enrolled according to the inclusion and exclusion criteria. The expressions of periostin and Smad2/3 in the tumor specimens were examined by immunohistochemistry. Results: Periostin expression of CAFs and cancer cells in the 351 CRC cases was observed at 36.8% and 0.6%, respectively. Smad2/3 expression of CAFs and cancer cells was observed in 41.0% and 90.0%, respectively. In CAFs, high periostin expression was significantly correlated with high Smad2/3 expression, increased invasion depth, lymph node metastasis, venous invasion, advanced disease stage, and a higher rate of relapse. The prognoses of patients with periostin-positive CAFs were significantly poorer than those with periostin-negative CAFs (p < 0.001). The survival outcomes of stage 3 CRC patients with co-expression of periostin and Smad2/3 were significantly worse compared to those with stage 2 CRC. In the stage 3 group, multivariate analysis revealed that periostin was an independent prognostic factor, while univariate analysis showed that both periostin and Smad2/3 were significantly correlated with poor survival. Conclusions: These findings suggest that periostin is expressed mainly in CAFs in CRC and is correlated with Smad2/3 expression in CAFs. Periostin from CAFs might be associated with the malignant progression of CRC via Smad2/3 signaling. Full article
(This article belongs to the Collection New Treatment for Colorectal Cancer)
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<p>Representative cases showing the expressions of periostin and Smad2/3 expression in colorectal cancer, stained with hematoxylin and eosin (H&amp;E). Periostin was expressed mainly in the cytoplasm of stromal cells. Smad2/3 was expressed mainly in the cytoplasm of cancer cells. The immunoreactivity of periostin and Smad2/3 was evaluated according to the intensity of staining categorized into four levels: 0 = negative, 1 = weak moderate, 2 = moderate, and 3 = intense.</p>
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<p>Kaplan–Meier survival curves. (<b>A</b>) The overall survival (OS) of the patients with periostin-positive tumor stroma was significantly poorer than that of the patients with periostin-negative tumors. Among the patients with stage 3 disease, the OS of those with periostin-positive tumor stroma was significantly poorer than that of the patients with periostin-negative tumors (<span class="html-italic">p</span> &lt; 0.001), and positive periostin expression was significantly associated with poorer survival rates compared to the negative-expression group. (<b>B</b>) The OS of the patients with Smad2/3-positive tumors was significantly poorer than that of the patients with Smad2/3-negative tumors (<span class="html-italic">p</span> &lt; 0.001). Among the stage 3 patients (<span class="html-italic">p</span> &lt; 0.001) compared to stage 2 (<span class="html-italic">p</span> = 0.330), the patients who were positive for Smad2/3 expression showed significantly poorer OS compared to the Smad2/3-negative patients. (<b>C</b>) The OS of the patients with both-expression-positive tumors was significantly poorer than that of the patients with either-expression-negative tumors (<span class="html-italic">p</span> &lt; 0.001). In stage 3 (<span class="html-italic">p</span> &lt; 0.001) compared to stage 2 (<span class="html-italic">p</span> = 0.015), the positive group for co-expression was significantly associated with poorer OS compared to the negative group. Both-expression-positive: periostin+/Smad2/3+. Either-expression-negative: periostin−/Smad2/3−, periostin+/Smad2/3−, and periostin−/Smad2/3.</p>
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12 pages, 992 KiB  
Article
Efficacy and Safety of the Topotecan–Cyclophosphamide Regimen in Adult Metastatic Ewing Sarcoma: A Large, Multicenter, Real-World Study
by Salih Tunbekici, Haydar Cagatay Yuksel, Caner Acar, Gokhan Sahin, Oguzcan Kınıkoglu, Nargiz Majidova, Mustafa Alperen Tunç, Mürsel Sali, Adem Deligonul, Berkan Karadurmus, Ibrahim Tunbekici, Pınar Gursoy, Ulus Ali Sanli and Erdem Goker
Cancers 2025, 17(3), 550; https://doi.org/10.3390/cancers17030550 - 6 Feb 2025
Viewed by 594
Abstract
Background/Objectives: There is an unmet need to improve outcomes in patients with metastatic Ewing sarcoma (ES). This retrospective, multicenter study aimed to evaluate the efficacy and safety of the topotecan–cyclophosphamide (TC) regimen in adult patients with metastatic ES who had previously been treated [...] Read more.
Background/Objectives: There is an unmet need to improve outcomes in patients with metastatic Ewing sarcoma (ES). This retrospective, multicenter study aimed to evaluate the efficacy and safety of the topotecan–cyclophosphamide (TC) regimen in adult patients with metastatic ES who had previously been treated with chemotherapy. Methods: This study enrolled 75 patients who were treated at five oncology centers in Turkey between 2011 and 2020. Patients were treated with the TC regimen, consisting of topotecan at 0.75 mg/m2/day and cyclophosphamide at 250 mg/m2/day, given daily for 5 days and repeated every 21 days. Results: The median progression-free survival was 3.06 months (95% CI, 2.91–3.22), and the median overall survival was 6.16 months (95% CI, 5.14–7.18). Patients who received the TC regimen in the second line demonstrated longer OS (7.55 months 95% CI, 5.37–14.17) compared to those who received it in the third line or later (5.70 months 95% CI, 4.07–6.60) (p = 0.005). When the TC regimen was used in the second line, the disease control rate was 50%, whereas in the third line or later, the DCR was 10.8%. In the entire group, the DCR was 30.7%. The most common toxicity was transient cytopenia. Conclusions: This study showed that the use of the TC regimen in the second line resulted in better efficacy and overall survival outcomes compared to its use in the third line or later. However, in the entire population, the TC regimen demonstrated only a modest effect on metastatic ES. TC can be considered one of the palliative treatment options for metastatic ES. Full article
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<p>Kaplan–Meier plot of topotecan–cyclophosphamide treatment. Median PFS was 3.06 months (95% CI, 2.91–3.22).</p>
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<p>Kaplan–Meier plot of topotecan–cyclophosphamide treatment. Median OS was 6.16 months (95% CI, 5.14–7.18).</p>
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<p>Forest plot for univariate Cox proportional hazards regression analyse. The horizontal bars in the forest plot represent the 95% confidence intervals for the hazard ratios. Variables where the confidence interval crosses the vertical line at HR = 1 were not statistically significant. Abbreviations: HR: hazard ratio; CI: confidence interval; ECOG PS: Eastern Cooperative Oncology Group Performance Status.</p>
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4 pages, 4318 KiB  
Correction
Correction: Xu et al. Hyaluronic Acid Interacting Molecules Mediated Crosstalk between Cancer Cells and Microenvironment from Primary Tumour to Distant Metastasis. Cancers 2024, 16, 1907
by Yali Xu, Johannes Benedikt and Lin Ye
Cancers 2025, 17(3), 549; https://doi.org/10.3390/cancers17030549 - 6 Feb 2025
Viewed by 377
Abstract
In the original publication [...] Full article
(This article belongs to the Section Cancer Metastasis)
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<p>Subcellular location of HAIMs. Differences in the distribution of the HAIMs indicate a wide range of biological functions affected by these molecules. The figure was created with BioRender (<a href="http://www.Biorender.com" target="_blank">www.Biorender.com</a>, accessed on 8 May 2024).</p>
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<p>Protein structure of HAIMs. Domain architecture of HAIMs. The link domain on the N-terminal of TSG-6, CD44, LYVE-1, HAPLNs and lecticans is the HA-binding domain, while in RHAMM, BX7B motif helps to bind HA. The G1 domain in the lecticans is responsible for HA binding; the G3 domain binds to ECM molecules like Tenascin and carbohydrate, including GAGs on the cell membrane. G2 domain is only found in ACAN, but its function remains unknown. CUB = C1r/C1s, Uegf, Bmp1; Within the BX7B motif, B = arginine (R) or lysine (K); X = non-acidic amino; GAG = glycosaminoglycans; EGF = epidermal growth factor (EGF)-like motif; CRP = complement regulatory protein repeat. This figure was created with <a href="http://www.BioRender.com" target="_blank">www.BioRender.com</a> (accessed on 8 May 2024).</p>
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<p>Interactions between HAIMs and HA in the ECM. HAIMs interact with HA to organise ECM. HA is produced directly by HAS. TSG-6 and VCAN assist with the transport of HC from IαI family members to HA chains. HCs linked to HA chains via ester bond and Pre-α-trypsin inhibitor are released. PTX3 helps with further HA organisation in the mammalian oocytes complex matrix. TSG-6 itself interacts with CD44 and enables CD44 to form a complex with HA. The induction of dimerization in TSG-6 by HA leads to the crosslinking of the HA polysaccharide. HAPLNs binding on the G1 domain of lecticans and tenascin’s binding to lecticans on their G3 domain also help to construct HA scaffold. PTX3 = Pentraxin-3; HC = heavy chain. This figure was created with BioRender (<a href="http://www.Biorender.com" target="_blank">www.Biorender.com</a>, accessed on 8 May 2024).</p>
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<p>HAIMs modulate cellular functions and the dissemination of cancer cells by interacting with ECM components. HAIMs from cancer cells, immune cells and mesenchymal cells all contributed to the abnormal HAIM levels in tumours. These HAIMs either function alone or form complexes with other HAIMs and ECM components including HA to alter malignant cellular behaviours. Cleavage of lecticans will affect their function. Various colours are used for indicating different molecules. Arrows are used to show their promoting effects. MMP = matrix metalloproteinase; ADAMTS = A disintegrin and metalloproteinase with thrombospondin motifs; FAP = fibroblast activation protein; EGFR = epidermal growth factor receptor. The figure was prepared with BioRender (<a href="http://www.Biorender.com" target="_blank">www.Biorender.com</a>, accessed on 8 May 2024).</p>
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<p>The molecular machinery of CD44, TSG-6, HAPLN and RHAMM regulated tumour proliferation, movement and metastasis. TSG-6 can facilitate CD44-EGFR interaction. HA/CD44 complex enhances EGFR-promoted cell proliferation and EMT via the RAS/TAF/MEK/ERK pathway. Membrane-anchored RHAMM–HA interaction activates RHO/ROCK pathway and therefore promoted cell migration and proliferation via unknown transmembrane receptors. Intercellular RHAMM enter the nucleus and binds to and stabilizes TPX2 to activate AURKA, leading to enhanced proliferation and migration. TSG-6 converts normal fibroblasts to CAF and therefore promotes CRC metastasis. RHAMM/CD44 complex also promotes EMT with the involvement of TGF-β1. AUKA = Aurora kinase A; TGFβ = transforming growth factor beta; EMT = epithelial–mesenchymal transition; EGFR = epidermal growth factor receptor. Created with BioRender (<a href="http://www.Biorender.com" target="_blank">www.Biorender.com</a>, accessed on 8 May 2024).</p>
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<p>HAIMs’ involvement in angiogenesis and lymphangiogenesis. VCAN, TSG-6, RHAMM and CD44 contribute to angiogenesis while SHAP, LYVE-1 and HAPLNs are involved in lymph angiogenesis and lymph node metastasis. Various colours are used for the purpose of grouping, indicating distinct molecular functions. VEGF = vascular endothelial growth factor; TGFβ = transforming growth factor beta; uPA = urokinase-type plasminogen activator; bFGF = basic fibroblast growth factor; CXCR4/CXCL12 = chemokine (C-X-C motif) receptor 4/chemokine (C-X-C motif) ligand 12. Created with BioRender (<a href="http://www.Biorender.com" target="_blank">www.Biorender.com</a>, accessed on 8 May 2024).</p>
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<p>HAIMs’ involvement in immune regulation. Various colours are used for the purpose of grouping, indicating distinct molecular functions. HC = heavy chain; PTX-3 = pentraxin-3; IL = interleukin; TNF = tumour necrosis factor; TLR = toll-like receptor. Created with BioRender (<a href="http://www.Biorender.com" target="_blank">www.Biorender.com</a>, accessed on 8 May 2024).</p>
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16 pages, 5421 KiB  
Article
Trends in Incidence and Mortality of Head and Neck Cancer Subsites Among Elderly Patients: A Population-Based Analysis
by Małgorzata Wierzbicka, Wioletta Pietruszewska, Adam Maciejczyk and Jarosław Markowski
Cancers 2025, 17(3), 548; https://doi.org/10.3390/cancers17030548 - 6 Feb 2025
Viewed by 608
Abstract
The incidence of head and neck cancer (HNC) has significantly increased over the past two decades. Material and methods: This study analyzed trends in HNC incidence and mortality using data from the Polish Cancer Register (1999–2021) across three age cohorts (60–69, 70–79, and [...] Read more.
The incidence of head and neck cancer (HNC) has significantly increased over the past two decades. Material and methods: This study analyzed trends in HNC incidence and mortality using data from the Polish Cancer Register (1999–2021) across three age cohorts (60–69, 70–79, and 80+) and projected trends through to 2035. Statistical analyses included regression, correlation, and parallelism tests, with significance levels of α = 0.05 and Bonferroni correction applied (αc ≈ 0.017). Results: In the 60–69 cohort, incidence rates increased faster than mortality rates (p < 0.001), especially for oral and oropharyngeal cancers in women (p < 0.001). For the 70–79 cohort, mortality rates rose slower than incidence (p < 0.05), most notably for salivary gland cancers across genders and oral cavity cancers in women. In the 80+ group, both incidence and mortality increased (p < 0.05), but mortality rates rose faster for laryngeal, hypopharyngeal, and oral cancers in men and the general population (p < 0.017). The largest increases were observed in oral cancer among women, with a marked rise across all age groups (p < 0.001). Gender-specific patterns highlighted stable or modestly rising trends in males but a notable increase in females, particularly in the 80+ group. Conclusions: These findings underscore that older patients are not a homogeneous group in terms of HNC incidence and survival. This study emphasizes age- and gender-specific strategies for prevention and management. Expanding HPV vaccination and improving early detection are crucial, particularly for high-risk groups like older women and those with HPV-related cancers. Tailored approaches could mitigate rising trends and improve survival outcomes. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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<p>Flowchart describing study group.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNSCC for the age cohort 80+; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999 − 2021. Head and neck squamous-cell carcinoma (HNSCC). (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNSCC cancers for the age cohort 80+; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999 − 2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the 80+ age cohort; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999 − 2021.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNSCC for the age cohort 80+; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999 − 2021. Head and neck squamous-cell carcinoma (HNSCC). (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNSCC cancers for the age cohort 80+; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999 − 2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the 80+ age cohort; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999 − 2021.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNCs for the age cohort 70–79; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNCs for the age cohort 70–79; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the age cohort 70–79; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNCs for the age cohort 70–79; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNCs for the age cohort 70–79; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the age cohort 70–79; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021.</p>
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<p>(<b>a</b>). Trend lines of the absolute number of cases of women with distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>b</b>). Trend lines of the absolute number of cases of men with distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021. (<b>c</b>). Trend lines of the absolute number of cases of distinguished groups of HNCs for the age cohort 60–69; dashed lines show the extrapolation of the trend to 2035 determined in the period 1999–2021.</p>
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<p>Trend lines for laryngeal cancer incidence by sex and age cohort in female (F), male (M), and total (T) populations from 1999 to 2021, stratified by age cohorts: 60–69 years, 70–79 years, and 80+ years. Parallelism tests were conducted to evaluate differences between trend lines for the analyzed age.</p>
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<p>Trend lines in the number of cases and deaths (larynx cancer) for women (F), men (M), and total (T) in the period 1999–2021, considering the age cohorts 60–69, 70–79, and 80+ (results of the test of parallelism of trend lines in the number of cases and number of deaths).</p>
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18 pages, 1299 KiB  
Article
Association Between Medicaid Expansion and Insurance Status, Risk Group, Receipt, and Refusal of Treatment Among Men with Prostate Cancer
by Tej A. Patel, Bhav Jain, Edward Christopher Dee, Khushi Kohli, Sruthi Ranganathan, James Janopaul-Naylor, Brandon A. Mahal, Kosj Yamoah, Sean M. McBride, Paul L. Nguyen, Fumiko Chino, Vinayak Muralidhar, Miranda B. Lam and Neha Vapiwala
Cancers 2025, 17(3), 547; https://doi.org/10.3390/cancers17030547 - 6 Feb 2025
Viewed by 556
Abstract
Background: Although the Patient Protection and Affordable Care Act (ACA) has been associated with increased Medicaid coverage among prostate cancer patients, the association between Medicaid expansion with risk group at diagnosis, time to treatment initiation (TTI), and the refusal of locoregional treatment [...] Read more.
Background: Although the Patient Protection and Affordable Care Act (ACA) has been associated with increased Medicaid coverage among prostate cancer patients, the association between Medicaid expansion with risk group at diagnosis, time to treatment initiation (TTI), and the refusal of locoregional treatment (LT) among patients requires further exploration. Methods: Using the National Cancer Database, we performed a retrospective cohort analysis of all patients aged 40 to 64 years diagnosed with localized prostate cancer from 2011 to 2016. Difference-in-difference (DID) analysis was used to compare changes in insurance status, risk group at diagnosis, TTI, and the refusal of LT among patients residing in Medicaid expansion versus non-expansion states. In a secondary analysis, we used DID to compare changes in the above outcomes among racial minorities versus White patients living in expansion states. Results: Of the 112,434 patients with prostate cancer in our analysis, 50,958 patients lived in Medicaid expansion states, and 61,476 patients lived in non-expansion states. In the adjusted analysis, we found that the proportion of uninsured patients (adjusted DID: −0.87%; 95% confidence interval [95% CI]: −1.28 to −0.46) and patients who refused radiation therapy (adjusted DID: −0.71%; 95% CI: −0.95 to −0.47) decreased more in expansion states compared to non-expansion states. Similarly, we observed that the racial disparity of select outcomes in expansion states narrowed, as racial minorities experienced larger absolute decreases in uninsured status and the refusal of radiation therapy (RT) regimens than White patients following ACA implementation (p < 0.01 for all). However, residence in a Medicaid expansion state was not associated with changes in risk group at diagnosis, TTI, nor the refusal of LT (p > 0.01 for all); racial disparities in TTI were also exacerbated in expansion states following ACA implementation. Conclusions: The association between Medicaid expansion and prostate cancer outcomes and disparities remains unclear. While ACA implementation was associated with increased insurance coverage and decreased refusal of RT, there was no significant association with earlier risk group at diagnosis, TTI within 180 days, or refusal of LT. Similarly, racial minorities in expansion states had larger decreases in uninsured status and the refusal of RT regimens, as well as smaller increases in intermediate-/high-risk disease at presentation than White patients following ACA implementation, but experienced no significant changes in TTI. More research is needed to understand how Medicaid expansion affects cancer outcomes and whether these effects are borne equitably among different populations. Full article
(This article belongs to the Special Issue Advances in Prostate Cancer Radiotherapy)
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<p>PRISMA diagram depicting cohort selection. Abbreviations: PCa: Prostate Cancer.</p>
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<p>Adjusted trends in health insurance status (Panel (<b>A</b>)), risk group at initial diagnosis (Panel (<b>B</b>)), timely treatment (Panel (<b>C</b>)), and refusal of RP and/or RT (Panel (<b>D</b>)). Participants include patients aged 40–64 years old diagnosed with prostate cancer between 1 January 2011 and 31 December 2016 from the National Cancer Database. Error bars show 95% confidence intervals of estimated margins. A vertical red line denotes the enactment of the Affordable Care Act (ACA) and Medicaid Expansion. Abbreviations: Radiation Therapy (RT), Radical Prostatectomy (RP).</p>
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11 pages, 225 KiB  
Article
A Longitudinal Study Examining the Impact of Chronic Rhinosinusitis on the Risk of Cancer Development: A National Population-Based Cohort Study
by Dong-Kyu Kim, Jae-In Kim, Il Hwan Lee and Dae-Soon Son
Cancers 2025, 17(3), 546; https://doi.org/10.3390/cancers17030546 - 6 Feb 2025
Viewed by 556
Abstract
Background/Objectives: We investigated the association between chronic rhinosinusitis (CRS) and cancer risk in an adult Korean population. Methods: This retrospective cohort study used data from the Korean National Health Insurance Service database. To ensure comparability between the groups, adjustments were made for potential [...] Read more.
Background/Objectives: We investigated the association between chronic rhinosinusitis (CRS) and cancer risk in an adult Korean population. Methods: This retrospective cohort study used data from the Korean National Health Insurance Service database. To ensure comparability between the groups, adjustments were made for potential confounding factors, including sex, age, residence, household income, diabetes, hypertension, and chronic kidney disease. The primary endpoint was the presence of newly diagnosed cancer. Results: Among 1,337,120 individuals in the nationally representative cohort database, 10,567 patients with CRS were identified and matched with 42,268 control subjects without CRS. Patients with CRS had a significantly higher risk of overall cancer events than controls. The adjusted hazard ratio (HR) for cancer in the CRS group was 1.16 (95% confidence interval [CI]: 1.05–1.28). Notably, female patients with CRS had an elevated risk of incident cancer events. Furthermore, patients with CRS without nasal polyps exhibited a significantly increased risk of cancer, whereas those with CRS with nasal polyps did not show a similar association. Conclusions: These findings underscore the need for physicians to carefully monitor patients with CRS for potential cancer progression and develop appropriate therapeutic strategies to mitigate the impact of this condition. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
15 pages, 262 KiB  
Review
Molecular Biomarkers in Borderline Ovarian Tumors: Towards Personalized Treatment and Prognostic Assessment
by Stefania Drymiotou, Efthymia Theodorou, Kathrine Sofia Rallis, Marios Nicolaides and Michail Sideris
Cancers 2025, 17(3), 545; https://doi.org/10.3390/cancers17030545 - 6 Feb 2025
Viewed by 617
Abstract
Borderline Ovarian Tumours (BOTs) are a heterogenous group of ovarian neoplasms which have increased mitotic activity but lack stromal invasion. We performed a narrative review of the literature, aiming to identify prognostic molecular biomarkers that can potentially be used for treatment personalisation. We [...] Read more.
Borderline Ovarian Tumours (BOTs) are a heterogenous group of ovarian neoplasms which have increased mitotic activity but lack stromal invasion. We performed a narrative review of the literature, aiming to identify prognostic molecular biomarkers that can potentially be used for treatment personalisation. We identified and discussed BRAF/KRAS, Cancer Antigen 125 (Ca 125), Calprotectin, p16ink4a, and Microsatellite instability (MSI) as the most studied biomarkers related to BOTs. Overall, BRAF and KRAS mutations are associated with earlier-stage and favourable prognosis; KRASmt may indicate extraovarian disease in serous BOT (sBOT). Ca125, the only currently clinically used biomarker, can be assessed pre-operatively and has an established role in post-operative surveillance, especially when it is raised pre-operatively or a high potential for malignant transformation is suspected post-operatively. p16ink4a expression trends could also indicate the malignant transformation of the tumour. Calprotectin has an inferior specificity to Ca125 and is not yet established as a biomarker, whilst there is very limited evidence available for MSI. As new evidence is coming along with artificial intelligence platforms, these biomarkers can be integrated and used towards the development of a precision model for treatment stratification and counselling in women diagnosed with BOTs. Full article
(This article belongs to the Special Issue Diagnostic Biomarkers in Cancers Study)
10 pages, 465 KiB  
Article
Long-Term Results of Intensity Modulated Radiotherapy (IMRT) with Helical Tomotherapy in Non-Metastatic Breast Cancer Patients: Final Analysis
by Pierre Loap, Abdelkarim Uakkas, Sofiane Allali, Jihane Bouziane, Alain Fourquet and Youlia Kirova
Cancers 2025, 17(3), 544; https://doi.org/10.3390/cancers17030544 - 6 Feb 2025
Viewed by 459
Abstract
Background: Intensity modulated radiotherapy with helical tomotherapy (IMRT-HT) is used in the breast cancer (BC) treatment for years now to obtain homogeneous dose distribution in the treated volumes and reduce the doses to organs at risk. The purpose of this study was to [...] Read more.
Background: Intensity modulated radiotherapy with helical tomotherapy (IMRT-HT) is used in the breast cancer (BC) treatment for years now to obtain homogeneous dose distribution in the treated volumes and reduce the doses to organs at risk. The purpose of this study was to evaluate our experience in terms of local control, overall survival, progression free survival and adverse events in BC patients treated with IMRT-HT with long term follow-up. Methods: This study is a retrospective data analysis of patients irradiated with IMRT-HT. Overall survival (OS) and progression free survival (PFS) curves were plotted with Kaplan-Meier method. We also analyzed the OS and PFS data by molecular subgroups of the population. Long-term toxicities including skin, cardiac and pulmonary complications were also evaluated. Multivariant logistic regression analysis was performed to determine the independent predictors of the side effects. Results: Between 2009 and 2015, a total of 194 breasts in 179 women with nonmetastatic breast cancer were treated. Most of the tumors were grade III and N+. With a median follow-up of 10 years, we observed 9 local recurrences, 2 loco-regional recurrences, and 29 patients experienced metastatic disease. Only 18 patients are dear, of them 7 cases with breast cancer death. At 10 years, the Local recurrence free survival was 95.3% [95%CI: 92.1–98.5], the loco-regional relapse free survival was 94.5% [91.1–98.1]. The metastases free survival was 82.9% [76.9–89.3]. The progression free survival was 79.9 [73.6–86.7]. The cancer specific survival was 94.3%, and the overall survival 88% [82.8–93.5]. At long term, there were no cardiac, lung, thyroid, digestive radio induced toxicities. A small number of patients experienced grade I or II fibrosis. Conclusions: IMRT-HT could be safely used for adjuvant breast cancer irradiation in patients with complex anatomy. IMRT-HT provides favourable long-term prognosis, while late toxicity is acceptable. Full article
(This article belongs to the Special Issue Advances in Invasive Breast Cancer: Treatment and Prognosis)
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<p>Overall survival (OS, <b>A</b>), cancer specific survival (CSS, <b>B</b>), local relapse free survival (LRFS, <b>C</b>), locoregional relapse free survival (LRRFS, <b>D</b>), metastasis-free survival (MFS, <b>E</b>), and progression free survival (PFS, <b>F</b>) of the study population.</p>
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8 pages, 978 KiB  
Perspective
Ozone–Oxygen Therapy to Prevent HPV-Related Cancers of the Lower Gynecological Tract in Infected Patients: The Rationale for Further Developments
by Luca Roncati
Cancers 2025, 17(3), 543; https://doi.org/10.3390/cancers17030543 - 6 Feb 2025
Viewed by 732
Abstract
Background: O3-O2 therapy is an alternative medical treatment that introduces a mixture of O3-O2 into the body for therapeutic purposes. The objective of this study is to evaluate its margins of applicability in the eradication of HPV [...] Read more.
Background: O3-O2 therapy is an alternative medical treatment that introduces a mixture of O3-O2 into the body for therapeutic purposes. The objective of this study is to evaluate its margins of applicability in the eradication of HPV infection from the lower gynecological tract by means of vaginal insufflation. Methods: An in-depth review of the international literature on this topic is carried out; in addition, O3-O2 therapy is compared with other treatments currently available in terms of its advantages, disadvantages, and exploited technologies. Results: The possible benefits and limitations of O3-O2 vaginal insufflation are explained in detail; overall, it appears to be an interesting tool as part of complex management to prevent HPV-related cancers of the lower gynecological tract in infected patients. Conclusions: The rationale and guidelines of this innovative procedure have been successfully illustrated, providing the technical specifications for further developments. Full article
(This article belongs to the Section Infectious Agents and Cancer)
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<p>Percentage of distribution by infectious agents of global cancer cases among females attributable to infections in 2020 (total attributable cases: 1,200,000.00) with a focus on the four most prevalent agents, i.e., HPV, Hp (Helicobacter pylori), HBV (hepatitis B-virus), and HCV (hepatitis C-virus) [data source: Globocan].</p>
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<p>An O<sub>3</sub>-O<sub>2</sub> therapy probe for vaginal insufflation: the central input of the vaginal insert (white) must be connected to a medical O<sub>3</sub> generator, while the lateral output of the insert is connected in series by means of a silicon tube with a liquid collector (green) and an O<sub>3</sub> destructor (black) to avoid gas leaks in the room. The concentric multi-ring thread of the vaginal insert is also designed to prevent O<sub>3</sub> leakage during treatment.</p>
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19 pages, 3338 KiB  
Article
Intra-Tumoral CD8+:CD3+ Lymphocyte Density Ratio in Appendix Cancer Is a Tumor Volume- and Grade-Independent Predictor of Survival
by Chelsea Knotts, Hyun Park, Christopher Sherry, Rose Blodgett, Catherine Lewis, Ashten Omstead, Kunhong Xiao, William LaFramboise, David L. Bartlett, Neda Dadgar, Ajay Goel, Ali H. Zaidi and Patrick L. Wagner
Cancers 2025, 17(3), 542; https://doi.org/10.3390/cancers17030542 - 6 Feb 2025
Viewed by 569
Abstract
Background: The immune contexture of solid tumors plays a critical role in cancer progression and response to immunotherapy. However, immunologic characterization of appendiceal cancer (AC) has lagged behind advancements in other gastrointestinal malignancies. This study aims to define the AC immune microenvironment by [...] Read more.
Background: The immune contexture of solid tumors plays a critical role in cancer progression and response to immunotherapy. However, immunologic characterization of appendiceal cancer (AC) has lagged behind advancements in other gastrointestinal malignancies. This study aims to define the AC immune microenvironment by quantifying CD3+ and CD8+ lymphocyte densities and assessing their prognostic significance. Methods: Archival tissue samples from 95 AC patients were analyzed using immunohistochemistry to assess CD3+ and CD8+ T cell densities and their ratios. Associations between lymphocyte density and clinical, pathologic, and oncologic variables were examined using Spearman’s correlation, Kruskal–Wallis tests, and Cox proportional hazards analysis. Results: Tumor samples exhibited substantial immunologic heterogeneity with significant rightward skew. CD3+ and CD8+ densities were higher in low-grade tumors (p = 0.02 and p = 0.01, respectively) and low-grade histologic subtypes (p = 0.01 and p = 0.006). Lymphocyte density was inversely associated with patient age and was significantly lower in high-grade and non-mucinous tumors. The CD8+:CD3+ ratio emerged as an independent prognostic marker for progression-free survival (HR = 0.39, p = 0.004), whereas absolute CD3+ and CD8+ densities were less predictive. Conclusions: This study highlights the diverse immune microenvironment in AC, with immune infiltration patterns correlating with tumor grade and histologic subtype. The CD8+:CD3+ ratio is a potential prognostic biomarker for patient stratification, underscoring its clinical significance. Future studies should expand immune biomarker panels and explore immunomodulatory therapies for lymphocyte-rich AC subsets. Full article
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<p>Immunohistochemical intra-tumoral lymphocyte staining of appendiceal cancer in various grades. CD3+ lymphocytes and CD8+ lymphocytes are represented on the left and right sides, respectively. (<b>A.1</b>) (with magnified field in (<b>A.2</b>)) represents a grade 1 LAMN with high CD3+ density within the submucosa and lamina propria (889.0 cells/mm<sup>2</sup>). (<b>B.1</b>) (with magnified field in (<b>B.2</b>)) represents a grade 2 AC NOS with intermediate CD3+ density within the lamina propria (568.7 cells/mm<sup>2</sup>). (<b>C.1</b>) (with magnified field in (<b>C.2</b>)) represents a grade 3 mAC with low CD3+ density within the submucosa and lamina propria (442.2 cells/mm<sup>2</sup>). (<b>D.1</b>) (with magnified field in (<b>D.2</b>)) represents a grade 1 mAC with high CD8+ density within the lamina propria (1366.4 cells/mm<sup>2</sup>) surrounding globules of acellular mucin for which the area of was excluded in our analysis of the region of interest. (<b>E.1</b>) (with magnified field in (<b>E.2</b>)) represents a grade 2 LAMN with intermediate CD3+ density within the lamina propria (316.4 cells/mm<sup>2</sup>). (<b>F.1</b>) (with magnified field in (<b>F.2</b>)) represents a grade 3 mAC with low CD3+ density within the submucosa (25.8 cells/mm<sup>2</sup>) as well as high lymphocytic densities within the mucosa, which was excluded in our analysis of intra-tumoral cellular densities. Red arrows depict examples of and are adjacent to either chromogen red or brown positive lymphocytes which were selected for in our analysis.</p>
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<p>Distribution of Lymphocyte Density in Appendiceal Cancer. This histogram represents the distribution of <b>CD3+</b> (purple) and <b>CD8+</b> (red) lymphocyte densities across the cohort. The overall CD3+ cell density (median 397.9 cells/mm<sup>2</sup>; 95% CI [206.0, 756.9]) exceeded the CD8+ cell density (median 225.6 cells/mm<sup>2</sup>; 95% CI [105.2, 415.1]). The distribution was non-normal, exhibiting rightward skew and kurtosis (<span class="html-italic">p</span> &lt; 0.0001 for both CD3+ and CD8+ densities). The purple bars represent the density of CD3+ T cells, which include all T lymphocytes, whereas the red bars represent the subset of CD8+ cytotoxic T cells, which inherently express CD3 as part of the T cell receptor complex.</p>
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<p>Comparison of four distinct and a subclassified histotype group including low grade appendiceal mucinous neoplasm (LAMN), mucinous adenocarcinoma (mAC), goblet cell adenocarcinoma (gcAC), signet ring cell adenocarcinoma (srcAC), and adenocarcinoma not otherwise specified (AC NOS). Among histologic tumor types, LAMN contained the highest density (589.3 [374.0, 1243.2]) of both CD3+ (<span class="html-italic">p</span> = 0.02). There was no statistical difference in CD8 densities, although LAMN had the highest concentrations (287.9 [152.2, 716.3], <span class="html-italic">p</span> &lt; 0.08).</p>
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<p>In low histologic grade, there was a strong association with higher CD3+ density (547.2 [338.6, 1095.8] compared to 309.2 [161.7, 593.0] and 310.9 [205.3, 558.6] for Grade 2 and Grade 3, respectively, <span class="html-italic">p</span> &lt; 0.02). Similarly, CD8+ density was also higher in low grade tumors (320.7 [184.8, 770.3] compared to 185.3 [86.3, 354.5] and 169.3 [68.2, 381.7] for Grade 2 and Grade 3, respectively, <span class="html-italic">p</span> &lt; 0.02).</p>
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<p>On univariable analysis, PFS was not associated with CD3+ or CD8+ cell densities or I-score but was associated with CD8+:CD3+ density ratio (HR 0.6, 95%CI [0.4, 1.0]); <span class="html-italic">p</span> = 0.04). For CD3+ and CD8+ cell density and I-score, the 70th percentile was selected as a cutoff by convention. On multivariable analysis, CD8+:CD3+ cell density ratio was independent of age, grade, and site of tissue biopsy (HR 0.39, 95%CI [0.20, 0.73], <span class="html-italic">p</span> = 0.004) and a predictor of improved PFS in appendix cancer.</p>
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17 pages, 1415 KiB  
Systematic Review
Acute and Chronic Cardiovascular Adverse Events in Patients with Acute Myeloid Leukemia: A Systematic Review
by Konstantinos C. Siaravas, Amalia I. Moula, Ioannis S. Tzourtzos, Christos E. Ballas and Christos S. Katsouras
Cancers 2025, 17(3), 541; https://doi.org/10.3390/cancers17030541 - 5 Feb 2025
Viewed by 935
Abstract
Background/Objectives: Patients with acute myeloid leukemia (AML) have a higher propensity for adverse cardiovascular outcomes, primarily due to the toxic effects of chemotherapeutic agents. The purpose of this systematic review is to explore the association of acute myeloid leukemia treatment with adverse cardiovascular [...] Read more.
Background/Objectives: Patients with acute myeloid leukemia (AML) have a higher propensity for adverse cardiovascular outcomes, primarily due to the toxic effects of chemotherapeutic agents. The purpose of this systematic review is to explore the association of acute myeloid leukemia treatment with adverse cardiovascular events. Methods: We systematically screened the literature for studies providing comparative data on cardiovascular toxicities in patients treated for acute myeloid leukemia. After the initial search, 3649 papers were screened and a final total number of 46 were included for the review process. Results: Common chemotherapeutic agents used in AML may cause cardiovascular (CV) toxicities. A plethora of pathophysiological mechanisms are incriminated for these effects. Drug combinations may increase the risk in a synergistic way. In addition, common mutations of AML, personal history of previous cardiovascular disease and impaired heart function carry an increased complication risk. Biomarkers, as well as multimodality imaging, may be used for the early detection of cardiovascular toxicities. Conclusions: Increased risks of CV toxicity and comorbidities are observed among AML patients. With all the available diagnostic modalities, early detection and CV prevention strategies can improve the patient’s prognosis and quality of life. Full article
(This article belongs to the Special Issue The Clinical Trials and Management of Acute Myeloid Leukemia)
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<p>Flowchart of the selection of studies after a systematic review of the literature.</p>
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<p>Cardiovascular toxicities caused by AML chemotherapy.</p>
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<p>Follow-up of patients receiving a HSCT. Abbreviations: HSCT: hematopoietic stem cell transplantation, ECG: electrocardiogram, TTE: transthoracic echocardiography.</p>
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<p>Timeline for the follow-up of high and very high-risk AML patients undergoing chemotherapy with anthracyclines. Abbreviations: ECG: electrocardiogram, TTE: transthoracic echocardiography.</p>
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17 pages, 2212 KiB  
Article
Advanced External Beam Stereotactic Radiotherapy for Skull Base Reirradiation
by He Wang, Fahed M. Alsanea, Dong Joo Rhee, Xiaodong Zhang, Wei Liu, Jinzhong Yang, Zhifei Wen, Yao Zhao, Tyler D. Williamson, Rachel A. Hunter, Peter A. Balter, Tina M. Briere, Ronald X. Zhu, Anna Lee, Amy C. Moreno, Jay P. Reddy, Adam S. Garden, David I. Rosenthal, Gary B. Gunn and Jack Phan
Cancers 2025, 17(3), 540; https://doi.org/10.3390/cancers17030540 - 5 Feb 2025
Viewed by 730
Abstract
Background/Objectives: Stereotactic body radiation therapy (SBRT) for skull base reirradiation is particularly challenging, as patients have already received substantial radiation doses to the region, and nearby normal organs may have approached their tolerance limit from prior treatments. In this study, we reviewed the [...] Read more.
Background/Objectives: Stereotactic body radiation therapy (SBRT) for skull base reirradiation is particularly challenging, as patients have already received substantial radiation doses to the region, and nearby normal organs may have approached their tolerance limit from prior treatments. In this study, we reviewed the characteristics and capabilities of four advanced external beam radiation delivery systems and four modern treatment planning systems and evaluated the treatment plan quality of each technique using skull base reirradiation patient cases. Methods: SBRT plans were generated for sixteen skull base reirradiation patients using four modalities: the GK plan for the Elekta Leksell Gamma Knife Perfexion/ICON, the CyberKnife (CK) plan for the Accuray CyberKnife, the intensity-modulated proton therapy (IMPT) plan for the Hitachi ProBeat-FR proton therapy machine, and the volumetric-modulated arc therapy (VMAT) plan for the Varian TrueBeam STx. These plans were evaluated and compared using two novel gradient indices in addition to traditional dosimetry metrics for targets and organs at risk (OARs). The steepest border gradient quantified the percent prescription dose fall-off per millimeter at the boundary between the target and adjacent critical structures. This gradient index highlighted the system’s ability to spare nearby critical OARs. The volume gradient assessed the extent of dose spread outside the target toward the patient’s body. Results: All plans achieved comparable target coverage and conformity, while IMPT and VMAT demonstrated significantly better uniformity. The GK plans exhibited the highest border gradient, up to 20.9%/mm, followed by small-spot-size IMPT plans and CK plans. Additionally, IMPT plans showed the benefit of reduced dose spread in low-dose regions and the lowest maximum and mean doses to the brainstem and carotid artery. Conclusions: The advanced external beam radiotherapy modalities evaluated in this study are well-suited for SBRT in skull base reirradiation, which demands precise targeting of tumors with highly conformal doses and steep dose gradients to protect nearby normal structures. Full article
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<p>A representative case showing SBRT plans from CyberKnife (CK), Gamma Knife (GK), intensity-modulated proton therapy (IMPT), and volumetric modulated arc therapy (VMAT) techniques. The patient initially received 70 Gy in 33 fractions in 2013 and underwent a VMAT SBRT for left nasopharynx recurrence in 2015 (20-month intervals). (<b>a</b>) The transverse view (top row) and sagittal view (bottom row) of the plan dose distributions. Several organs at risk surround the target, and the plans were generated to meet clinical goals outlined in <a href="#cancers-17-00540-t004" class="html-table">Table 4</a>. (<b>b</b>) Dose-volume histograms of the primary target, brainstem, and ipsilateral carotid for the same patient.</p>
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<p>A representative case showing SBRT plans from CyberKnife (CK), Gamma Knife (GK), intensity-modulated proton therapy (IMPT), and volumetric modulated arc therapy (VMAT) techniques. The patient initially received 70 Gy in 33 fractions in 2013 and underwent a VMAT SBRT for left nasopharynx recurrence in 2015 (20-month intervals). (<b>a</b>) The transverse view (top row) and sagittal view (bottom row) of the plan dose distributions. Several organs at risk surround the target, and the plans were generated to meet clinical goals outlined in <a href="#cancers-17-00540-t004" class="html-table">Table 4</a>. (<b>b</b>) Dose-volume histograms of the primary target, brainstem, and ipsilateral carotid for the same patient.</p>
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<p>Comparison of primary target coverage, Paddick conformity index, and homogeneity index for CyberKnife (CK), Gamma Knife (GK), intensity-modulated proton therapy (IMPT), and volumetric modulated arc therapy (VMAT).</p>
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<p>Comparison of the steepest border gradient (<b>left</b>) and volume gradient (<b>right</b>) for CyberKnife (CK) Gamma Knife (GK), intensity-modulated proton therapy (IMPT), and volumetric modulated arc therapy (VMAT).</p>
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<p>Comparison of the brainstem (<b>left</b>) and carotid (<b>right</b>) dose with one standard deviation for CyberKnife (CK), Gamma Knife (GK), intensity-modulated proton therapy (IMPT), and volumetric modulated arc therapy (VMAT). Doses are normalized to prescription doses.</p>
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13 pages, 1339 KiB  
Article
Body Composition Analysis in Metastatic Non-Small-Cell Lung Cancer: Depicting Sarcopenia in Portuguese Tertiary Care
by José Leão Mendes, Rita Quaresma Ferreira, Inês Mata, João Vasco Barreira, Ysel Chiara Rodrigues, David Silva Dias, Manuel Luís Capelas, Antti Mäkitie, Inês Guerreiro, Nuno M. Pimenta and Paula Ravasco
Cancers 2025, 17(3), 539; https://doi.org/10.3390/cancers17030539 - 5 Feb 2025
Viewed by 590
Abstract
Background/Objectives: Sarcopenia is an emergent prognostic biomarker in clinical oncology. Albeit increasingly defined through skeletal muscle index (SMI) thresholding, the literature cut-offs fail to discern heterogeneous baseline muscularity across populations. This study assesses the prognostic impact of using cohort-specific SMI thresholds in [...] Read more.
Background/Objectives: Sarcopenia is an emergent prognostic biomarker in clinical oncology. Albeit increasingly defined through skeletal muscle index (SMI) thresholding, the literature cut-offs fail to discern heterogeneous baseline muscularity across populations. This study assesses the prognostic impact of using cohort-specific SMI thresholds in a Portuguese metastatic non-small-cell lung cancer (mNSCLC) cohort. Methods: Retrospective study including mNSCLC patients treated between January 2017 and December 2022. ImageJ v1.54 g was used to assess cross-sectional CT imaging at the third lumbar vertebra (L3) and calculate L3SMI. Sarcopenia was defined both according to Prado et al. and L3SMI thresholds derived from receiver operating characteristic analysis. Overall survival (OS) was the primary endpoint. Secondary endpoints included first-line (1L) progression-free survival (PFS) and sarcopenia subgroup analysis regarding body mass index impact on OS. Results: The initial cohort included 197 patients. Mean age was 65 years (±11.31). Most tumors were adenocarcinomas (n = 165) and presented with metastasis (n = 154). SMI was evaluable in 184 patients: cohort-specific thresholds (<49.96 cm2/m2 for men; <34.02 cm2/m2 for women) yielded 46.74% sarcopenic patients (n = 86) versus 66.30% (n = 122) per the literature definition. Cohort-specific thresholds predicted both OS (12.75 versus 21.13 months, hazard ratio [HR] 1.654, p = 0.002) and PFS (7.92 versus 9.56 months, HR 1.503, p = 0.01). Among sarcopenic patients, overweight (HR 0.417, p = 0.01) and obesity (HR 2.723, p = 0.039) had contrasting impacts on OS. Conclusions: Amid reclassification of nearly one-fifth of the cohort, cohort-specific thresholds improved sarcopenia prognostication in mNSCLC. Homogeneity regarding both cancer treatment setting and ethnicity could be key to defining sarcopenia based on SMI. Full article
(This article belongs to the Section Clinical Research of Cancer)
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<p>(<b>a</b>) Overall survival in the skeletal muscle index-assessed cohort with sarcopenia defined according to Prado et al. Median overall survival was 17.9 months for sarcopenic patients versus 20.11 months for not sarcopenic patients (<span class="html-italic">p</span> = 0.58). (<b>b</b>) Overall survival in the skeletal muscle index-assessed cohort with sarcopenia defined according to the cohort-specific thresholds. Median overall survival was 12.75 months for sarcopenic patients versus 21.13 months for not sarcopenic patients (hazard ratio for death 1.654; <span class="html-italic">p</span> = 0.002).</p>
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<p>Forest plot for subgroup analysis of overall survival. CI, confidence interval; AJCC, American Joint Committee on Cancer; TKI, tyrosine kinase inhibitor; IO, immunotherapy; ChT, chemotherapy; and ChT/ChT + IO, chemotherapy or chemoimmunotherapy. Not overweight corresponds to a body mass index &lt; 25 kg/m<sup>2</sup>, i.e., underweight or normal weight and overweight corresponds to a body mass index ≥ 25 kg/m<sup>2</sup>, i.e., overweight or obese.</p>
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<p>Overall survival in sarcopenic patients according to BMI. BMI, body mass index. Underweight corresponds to a BMI &lt; 18.5 kg/m<sup>2</sup>; normal weight corresponds to a BMI ≥ 18.5 kg/m<sup>2</sup> and &lt;25 kg/m<sup>2</sup>; overweight corresponds to BMI ≥ 25 kg/m<sup>2</sup> and &lt;30 kg/m<sup>2</sup>; and obesity corresponds to BMI ≥ 30 kg/m<sup>2</sup>.</p>
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Article
Risk Factors and Long-Term Outcomes of Acute Kidney Disease in Hematopoietic Stem Cell Transplant—Cohort Study
by Natacha Rodrigues, Carolina Branco, Gonçalo Sousa, Manuel Silva, Cláudia Costa, Filipe Marques, Pedro Vasconcelos, Carlos Martins and José António Lopes
Cancers 2025, 17(3), 538; https://doi.org/10.3390/cancers17030538 - 5 Feb 2025
Viewed by 480
Abstract
Background: Acute kidney disease (AKD) is a recent definition reflecting ongoing physiopathological processes of an acute renal injury (AKI). Information on AKD in hematopoietic stem cell transplant (HSCT) is scarce and there is no available data on long-term outcomes. We aimed to determine [...] Read more.
Background: Acute kidney disease (AKD) is a recent definition reflecting ongoing physiopathological processes of an acute renal injury (AKI). Information on AKD in hematopoietic stem cell transplant (HSCT) is scarce and there is no available data on long-term outcomes. We aimed to determine the cumulative incidence of AKD in the first 100 days after HSCT; to identify risk factors for AKD in HSCT; and to determine the impact of AKD in 3-year overall survival and relapse-free survival in HSCT. Methods: A retrospective cohort study was conducted, considering AKD when AKI was present and the patient continued to meet the KDIGO criteria (creatinine and/or urinary output criteria) for 7 days or more. Survival analysis methods considering competing events were used for risk factors and disease-free survival, Cox proportional regression for overall survival, and stepwise regression methods for multivariable models. Results: We enrolled 422 patients. AKD incidence was 22.9% (95% CI: 19.2–27.4%). Higher body mass index (HR: 1.05, 95% CI 1.01–1.10; p = 0.034), HCT-CI score ≥ 2 (HR: 1.83, 95% CI 1.11–3.13; p = 0.027), allogeneic transplantation (HR:2.03, 95% CI 1.26–3.33; p = 0.004), higher C-reactive protein (HR:1.01, 95% CI 1.01–1.02; p < 0.001), and exposure to nephrotoxic drugs (HR: 4.81, 95% CI 1.54–4.95; p = 0.038) were independently associated with AKD. AKD had a significant impact on overall survival (HR: 1.75; 95% CI 1.27–2.39; p = 0.001). Conclusion: An awareness of the risk factors for AKD allows the identification of high-risk patients, enabling the timely implementation of preventive measures to alleviate the progression and impact of the disease. Full article
(This article belongs to the Section Cancer Therapy)
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<p>AKD cumulative incidence function in the first 100 days after HSCT. Death was considered a competing event. HSCT—hematopoietic stem cell transplant; CI—cumulative incidence; AKD—acute kidney disease.</p>
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<p>Overall survival considering AKD in the first 100 days after HSCT. HSCT—hematopoietic stem cell transplant; CI—cumulative incidence; AKD—acute kidney disease.</p>
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20 pages, 1338 KiB  
Article
Right-Sided Versus Left-Sided Colon Cancer—A 5-Year Single-Center Observational Study
by Julia Szostek, Michał Serafin, Magdalena Mąka, Beata Jabłońska and Sławomir Mrowiec
Cancers 2025, 17(3), 537; https://doi.org/10.3390/cancers17030537 - 5 Feb 2025
Viewed by 422
Abstract
Background: Global colorectal cancer (CRC) incidence is significant, constituting 15% of all cancer cases with 1.4 million new diagnoses annually. Recent research suggests categorizing CRC into three clinical groups: right colon cancer (RCC), left colon cancer (LCC), and rectal cancer, each with distinct [...] Read more.
Background: Global colorectal cancer (CRC) incidence is significant, constituting 15% of all cancer cases with 1.4 million new diagnoses annually. Recent research suggests categorizing CRC into three clinical groups: right colon cancer (RCC), left colon cancer (LCC), and rectal cancer, each with distinct embryological and molecular characteristics. Methods: A retrospective analysis of 189 patients (103 men, 86 women) undergoing surgery for RCC and LCC from January 2018 to December 2023 was performed. Results: LCC was a more common localization (98, 51.85%) than RCC (91, 48.15%). Patients with RCC were older than patients with LCC (70 (36–92, IQR 11) vs. 68 (38–84, IQR 12.5) years; p = 0.02). The duration of surgical procedure was comparable in both groups (225 (120–420, IQR 80) vs. 210 (105–505, IQR 85) minutes; p = 0.16). Complications occurred in 16 (17.58%) patients with RCC and in 15 (15.31%) patients with LCC (p = 0.72). One-year overall survival was 92.76% (SE 2.16%) (91.57% (SE 3.43%) in the RCC group and 93.99% (SE 2.61%) in the LCC group; p = 0.79). Conclusions: Colon cancer incidence is increasing globally due to economic and lifestyle factors. Our study reflects this trend, noting a rise in cases from 2018 to 2023. Despite several differences, overall survival rates do not significantly differ between RCC and LCC patients. Understanding clinical disparities is crucial for optimizing patient outcomes. Full article
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<p>Number of patients undergoing colectomy for right-sided or left-sided colon cancer for from January 2018 and December 2023.</p>
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<p>Overall survival rate of the series.</p>
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<p>Overall survival rate—right colon cancer vs. left colon cancer.</p>
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<p>Overall survival rate—Stage 0–II vs. Stage III–IV.</p>
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<p>Overall survival rate—Radical tumor resection vs. Palliative tumor resection.</p>
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12 pages, 569 KiB  
Article
Genomic Characterization of Chordoma: Insights from the AACR Project GENIE Database
by Beau Hsia, Gabriel Bitar, Saif A. Alshaka, Jeeho D. Kim, Bastien A. Valencia-Sanchez, Farhoud Faraji, Michael G. Brandel, Mariko Sato, John Ross Crawford, Michael L. Levy, Vijay A. Patel and Sean P. Polster
Cancers 2025, 17(3), 536; https://doi.org/10.3390/cancers17030536 - 5 Feb 2025
Viewed by 608
Abstract
Background: Chordoma is a rare primary tumor originating from embryonic notochord remnants, with limited systemic therapeutic options due to a poor understanding of its genomic landscape. This study aims to characterize the genetic alterations in chordoma using a large national patient-level genomic repository, [...] Read more.
Background: Chordoma is a rare primary tumor originating from embryonic notochord remnants, with limited systemic therapeutic options due to a poor understanding of its genomic landscape. This study aims to characterize the genetic alterations in chordoma using a large national patient-level genomic repository, the AACR Project GENIE, to identify potential therapeutic targets and improve disease modeling. Methods: A retrospective analysis of chordoma samples was conducted using the AACR Project GENIE database. Targeted sequencing data were analyzed for recurrent somatic mutations, tumor mutational burden, and chromosomal copy number variations, with significance set at p < 0.05. Results: Frequent mutations were observed in genes associated with SWI/SNF complex affecting chromatin remodeling (SETD2, PBRM1, ARID1A). Mutations were also common among the TERT promoter regions, and cell cycle regulation (CDKN2A). Significant co-occurrences were identified among PBRM1, BRCA2, and KMT2D mutations. CDKN2A/B deletions were enriched in metastatic tumors, and pediatric cases demonstrated distinct mutation profiles compared to adults. Conclusions: This study provides a genomic profile of chordoma, identifying key mutations and potential therapeutic targets. These findings highlight the roles of chromatin remodeling and cell cycle pathways in chordoma biology, offering insights for future precision medicine approaches and therapeutic interventions. Full article
(This article belongs to the Special Issue Feature Papers in Section “Cancer Informatics and Big Data”)
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<p>OncoPrint of recurrent mutations in chordoma (for genes with n ≥ 5, VAF ≥ 5%, coverage ≥ 100×). Star (*) indicates that not all samples were profiled.</p>
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36 pages, 1573 KiB  
Review
S-Adenosylmethionine: A Multifaceted Regulator in Cancer Pathogenesis and Therapy
by David Fernández-Ramos, Fernando Lopitz-Otsoa, Shelly C. Lu and José M. Mato
Cancers 2025, 17(3), 535; https://doi.org/10.3390/cancers17030535 - 5 Feb 2025
Viewed by 674
Abstract
S-adenosylmethionine (SAMe) is a key methyl donor that plays a critical role in a variety of cellular processes, such as DNA, RNA and protein methylation, essential for maintaining genomic stability, regulating gene expression and maintaining cellular homeostasis. The involvement of SAMe in cancer [...] Read more.
S-adenosylmethionine (SAMe) is a key methyl donor that plays a critical role in a variety of cellular processes, such as DNA, RNA and protein methylation, essential for maintaining genomic stability, regulating gene expression and maintaining cellular homeostasis. The involvement of SAMe in cancer pathogenesis is multifaceted, as through its multiple cellular functions, it can influence tumor initiation, progression and therapeutic resistance. In addition, the connection of SAMe with polyamine synthesis and oxidative stress management further underscores its importance in cancer biology. Recent studies have highlighted the potential of SAMe as a biomarker for cancer diagnosis and prognosis. Furthermore, the therapeutic implications of SAMe are promising, with evidence suggesting that SAMe supplementation or modulation could improve the efficacy of existing cancer treatments by restoring proper methylation patterns and mitigating oxidative damage and protect against damage induced by chemotherapeutic drugs. Moreover, targeting methionine cycle enzymes to both regulate SAMe availability and SAMe-independent regulatory effects, particularly in methionine-dependent cancers such as colorectal and lung cancer, presents a promising therapeutic approach. Additionally, exploring epitranscriptomic regulations, such as m6A modifications, and their interaction with non-coding RNAs could enhance our understanding of tumor progression and resistance mechanisms. Precision medicine approaches integrating patient subtyping and combination therapies with chemotherapeutics, such as decitabine or doxorubicin, together with SAMe, can enhance chemosensitivity and modulate epigenomics, showing promising results that may improve treatment outcomes. This review comprehensively examines the various roles of SAMe in cancer pathogenesis, its potential as a diagnostic and prognostic marker, and its emerging therapeutic applications. While SAMe modulation holds significant promise, challenges such as bioavailability, patient stratification and context-dependent effects must be addressed before clinical implementation. In addition, better validation of the obtained results into specific cancer animal models would also help to bridge the gap between research and clinical practice. Full article
(This article belongs to the Section Molecular Cancer Biology)
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<p>Overview of the methionine cycle, and connections with folate cycle, and transsulfuration pathway illustrating the role of SAMe in key cellular processes including nucleic acids, protein and lipid methylation, SAMe/SAH homeostasis and polyamine synthesis. SAMe molecule structure obtained from: <a href="https://3d.nih.gov/doi/11913/2" target="_blank">https://3d.nih.gov/doi/11913/2</a> (accessed on 16 December 2024). Gray: carbon; blue: nitrogen; red: oxygen; yellow: sulfur; white: hydrogen. ADO: adenosine; AMD: adenosylmethionine decarboxylase; BHMT: betaine HCYmethyltransferase; CBS: cystathionine beta-synthase; CTH: cystathionase; DNMTs: DNA methyltransferases; GNMT: glycine N-methyltrasferase; GSH: glutathione; KTMs: lysine-specific methyltransferases; MAT: methionine adenosyltransferase; METTL3/14: methyltransferase-like protein 3/14; MS: methionine synthase; MTs: methyltransferases; MTHFR: methylenetetrahydrofolate reductase; NNMT: nicotinamide N-methyltransferase; PC: phosphatidylcholine; PE: phosphatidylethanolamine; PEMT: phosphatidylethanolamine N-methyltransferase; PRMTs: protein arginine methyl transferases; SAH: S-adenosylhomocysteine; SAHH: S-adenosylhomocysteine hydrolase; SAMe: S-adenosylmethionine.</p>
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<p>Role of S-Adenosylmethionine in various cancers. The figure highlights tissue-specific changes in SAMe metabolism, DNA methylation patterns, and the expression of key enzymes in cancers of the prostate, lung, liver, breast, colorectal, gastric, and other tissues. SAMe molecule structure obtained from: <a href="https://3d.nih.gov/doi/11913/2" target="_blank">https://3d.nih.gov/doi/11913/2</a> (accessed on 16 December 2024). Gray: carbon; blue: nitrogen; red: oxygen; yellow: sulfur; white: hydrogen. ACSL3: acyl-CoA synthetase long chain family member 3; AK4: Adenylate kinase 4; AKT: Protein kinase B; AMD: SAMe decarboxylase proenzyme; AMD1: SAMe decarboxylase proenzyme 1; AMPK: AMP-activated protein kinase; ATF3: Activating transcription factor 3; CBS: Cystathionine beta-synthase; CIMP: CpG island methylator phenotype; DNMT1: DNA (cytosine-5)-methyltransferase 1; DOK7: Downstream of kinase 7; DUSP1: Dual-specificity MAPK phosphatase; ERα: Estrogen receptor α; ERK: Extracellular signal regulated kinase; ERRFI1: ERBB receptor feedback inhibitor 1; GIT1: G Protein Coupled Receptor Kinase Interacting ArfGAP 1; GNMT: Glycine N-methyltrasferase; GSTπ: Glutathione-S-transferase; H3K4: 4th lysine in Histone H3; H3K27: 27th lysine in Histone H3; HCC: Hepatocellular carcinoma; H-Ras: HRas proto-oncogene; JAK: Janus kinase; LARP1: La-Related Protein 1; LINE-1: Long interspersed nuclear element 1; LKB1: Serine/threonine protein kinase 11; m<sup>6</sup>A: N6-methyladenosine; MAT I/III: Methionine Adenosyltransferase I/III; MAT1A: Methionine Adenosyltransferase 1A; MAT2A: Methionine Adenosyltransferase 2A; MAT2B: Methionine Adenosyltransferase 2 Non-Catalytic Beta Subunit; MCD: Methionine and choline deficient; MDR1: Multidrug resistance 1; MeCP2:methyl-CpG-binding protein 2; METTL3: Methyltransferase-like protein 3; MGMT: O(6)-methylguanine DNA methyltransferase; MLH1: MutL Homolog 1; MMP-2: Matrix metalloproteinase-2; mSAMC: Mitochondrial S-adenosylmethionine carrier; MTAP: MTA phosphorylase; mTOR: Mammalian target of rapamycin; NNMT: Nicotinamide methyltransferase; ODC: Ornithine decarboxylase; PI3K: Phosphoinositide 3-kinase; PITX2: Paired like homeodomain transcription factor 2; PTEN: Phosphatase and tensin homolog; RIP1: receptor-interacting Protein 1; SAMe: S-adenosylmethionine; STAT3: Signal transducer and activator of transcription; uPA: Urokinase-type plasminogen activator.</p>
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21 pages, 4020 KiB  
Article
Trends in the Incidence and Mortality of Tobacco-Related Cancers Among Adults in the United States
by Nandika Mansingka, Victor Adekanmbi, Christine D. Hsu, Thao N. Hoang, Jacques G. Baillargeon, Abbey B. Berenson and Fangjian Guo
Cancers 2025, 17(3), 534; https://doi.org/10.3390/cancers17030534 - 5 Feb 2025
Viewed by 541
Abstract
Background: Tobacco use remains a global challenge to public health, accounting for almost eight million deaths per year worldwide, with a significant portion attributable to tobacco-related cancers. Examining the epidemiology of tobacco-related cancers and assessing the trends in the incidence and mortality will [...] Read more.
Background: Tobacco use remains a global challenge to public health, accounting for almost eight million deaths per year worldwide, with a significant portion attributable to tobacco-related cancers. Examining the epidemiology of tobacco-related cancers and assessing the trends in the incidence and mortality will allow for more effective prevention, treatment, and targeted strategies. Methods: We assessed the trends in the incidence and mortality of tobacco-related cancers among adults in the United States using data from United States Cancer Statistics (USCS) 2001–2021 and mortality data 1975–2022 from the National Center for Health Statistics (NCHS). The incidence and mortality rates of tobacco-related cancers were calculated as cases per 1,000,000 persons and age-adjusted to the 2000 United States standard population. Results: There was a recent overall decreasing trend in both the incidence (2001–2021) and mortality rate (2001–2022). Among adults 20–49 years old, there was an increasing trend from 2001 to 2021 in the incidence among non-Hispanic American Indians/Alaska Natives (APC 2.6, 95% CI 2.1–3.0) and those in the West (APC 0.2, 95% CI 0.0–0.4); in Hispanics, the incidence rate increased most recently from 2013 to 2021 (APC 1.7, 95% CI 1.0–3.0). The mortality rate first increased from 1975 to 1990 among females 50–64 years old and males 65+ years old and from 1975 to 2000 among females 65+ years old, and then decreased thereafter. Conclusions: The rising incidence in some younger groups highlights the need for targeted public health interventions to address disparities and improve cancer prevention in these vulnerable populations. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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<p>Adjusted incidence rates of tobacco-related cancers among adults in the United States from 2001 to 2021 by age group: (<b>A</b>) all; (<b>B</b>) 20–49 years old; (<b>C</b>) 50–64 years old; (<b>D</b>) 65+ years old. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults in the United States from 2001 to 2021 by age group: (<b>A</b>) all; (<b>B</b>) 20–49 years old; (<b>C</b>) 50–64 years old; (<b>D</b>) 65+ years old. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults 20–49 years old in the United States from 2001 to 2021 by race/ethnicity. (<b>A</b>) Hispanic. (<b>B</b>) Non-Hispanic White. (<b>C</b>) Non-Hispanic Black. (<b>D</b>) Non-Hispanic American Indian/Alaska Native. (<b>E</b>) Non-Hispanic Asian or Pacific Islander. NHW: Non-Hispanic White, NHB: Non-Hispanic Black, NHAIAN: Non-Hispanic American Indian/Alaska Native, NHAPI: Non-Hispanic Asian or Pacific Islander. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults 20–49 years old in the United States from 2001 to 2021 by race/ethnicity. (<b>A</b>) Hispanic. (<b>B</b>) Non-Hispanic White. (<b>C</b>) Non-Hispanic Black. (<b>D</b>) Non-Hispanic American Indian/Alaska Native. (<b>E</b>) Non-Hispanic Asian or Pacific Islander. NHW: Non-Hispanic White, NHB: Non-Hispanic Black, NHAIAN: Non-Hispanic American Indian/Alaska Native, NHAPI: Non-Hispanic Asian or Pacific Islander. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults 50–64 years old in the United States from 2001 to 2021 by race/ethnicity. (<b>A</b>) Hispanic. (<b>B</b>) Non-Hispanic White. (<b>C</b>) Non-Hispanic Black. (<b>D</b>) Non-Hispanic American Indian/Alaska Native. (<b>E</b>) Non-Hispanic Asian or Pacific Islander. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults 50–64 years old in the United States from 2001 to 2021 by race/ethnicity. (<b>A</b>) Hispanic. (<b>B</b>) Non-Hispanic White. (<b>C</b>) Non-Hispanic Black. (<b>D</b>) Non-Hispanic American Indian/Alaska Native. (<b>E</b>) Non-Hispanic Asian or Pacific Islander. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults 65 years and older in the United States from 2001 to 2021 by race/ethnicity. (<b>A</b>) Hispanic. (<b>B</b>) Non-Hispanic White. (<b>C</b>) Non-Hispanic Black. (<b>D</b>) Non-Hispanic American Indian/Alaska Native. (<b>E</b>) Non-Hispanic Asian or Pacific Islander. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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<p>Adjusted incidence rates of tobacco-related cancers among adults 65 years and older in the United States from 2001 to 2021 by race/ethnicity. (<b>A</b>) Hispanic. (<b>B</b>) Non-Hispanic White. (<b>C</b>) Non-Hispanic Black. (<b>D</b>) Non-Hispanic American Indian/Alaska Native. (<b>E</b>) Non-Hispanic Asian or Pacific Islander. Red dots indicate the cancer incidence, while the lines represent trends in cancer incidence over time.</p>
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18 pages, 2100 KiB  
Article
Distinct NF-kB Regulation Favors a Synergic Action of Pevonedistat and Laduviglusib in B-Chronic Lymphocytic Leukemia Cells Ex Vivo
by Víctor Arenas, Jose Luis Castaño, Juan José Domínguez, Lucrecia Yáñez and Carlos Pipaón
Cancers 2025, 17(3), 533; https://doi.org/10.3390/cancers17030533 - 5 Feb 2025
Viewed by 674
Abstract
Background/Objectives: Chronic lymphocytic leukemia (CLL) remains an incurable B-cell malignancy. B-CLL cells exhibit an extended lifespan in part due to the activation of survival pathways such as NF-kB. A crosstalk between NF-kB and GSK-3β pathways has been reported. NF-kB has also been identified [...] Read more.
Background/Objectives: Chronic lymphocytic leukemia (CLL) remains an incurable B-cell malignancy. B-CLL cells exhibit an extended lifespan in part due to the activation of survival pathways such as NF-kB. A crosstalk between NF-kB and GSK-3β pathways has been reported. NF-kB has also been identified as a primary target of the NEDD8-activating enzyme inhibitor MLN4924. Our objective was to investigate potential synergies of MLN4924 with other NF-kB-targeting agents for the treatment of CLL and elucidate the mechanisms of action underlying this pathway regulation. Methods: To assess the cytotoxic efficacy of the combined ex vivo treatment with CHIR-99021 and MLN4924, we employed 7-AAD staining and XTT viability assays on primary samples from CLL patients. Subsequently, we conducted various analyses to identify the molecular mechanisms underlying the cytotoxic effects of this combination. Results: We discovered a discrepancy between the mRNA and protein levels of IkBɑ and provided evidence of translational control over its expression. This observation may explain why, unlike other cell types, B-CLL cells did not activate NF-kB signaling following inhibition of GSK-3ß. Furthermore, we describe a synergistic effect between a specific GSK-3ß inhibitor, CHIR-99021/Laduviglusib, and the NEDD8-activating enzyme inhibitor MLN4924/Pevonedistat, at doses that only slightly affect healthy B cell viability ex vivo. We investigated the molecular basis of this co-induction of cell death by analyzing the alterations in apoptosis-related gene expression. We found that the combinational treatment enhances a reduction in BCL2 mRNA expression levels, providing an alternative approach for BCL-2 inhibition in CLL that could have therapeutic implications for the treatment of refractory CLL cases. Conclusions: our findings revealed a unique interaction between GSK-3ß and NF-kB pathways in CLL and their regulation of BCL2 expression. Full article
(This article belongs to the Section Molecular Cancer Biology)
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<p>Basal expression of <span class="html-italic">NFKBIA</span> and its encoded protein, IkBα in CLL. (<b>A</b>) RT-qPCR analysis of the indicated genes in B cells from healthy and CLL donors (n = 7 each). Results are presented relative to ß-actin. Statistical significance was determined using Student’s <span class="html-italic">t</span>-test. *** <span class="html-italic">p</span> &lt; 0.001, Student’s <span class="html-italic">t</span>-test. (<b>B</b>) Representative immunoblot analysis of whole cell extracts from chronic lymphocytic leukemia (CLL), monoclonal B-cell lymphocytosis (MBL) patients or healthy donors. (<b>C</b>) Densitometric analysis of the immunoblot bands for GSK-3, IkBα or p65/RelA relative to GAPDH in CLL or MBL patients or healthy donors. Groups were compared to healthy using Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, Student’s <span class="html-italic">t</span>-test. (<b>D</b>) Analysis of the effect of MLN4924 on the expression levels of GSK-3 and p65 proteins by western blot. PBMCs from CLL patients were treated ex vivo with 250 nM MLN4924 or 25 nM MLN7243/TAK243 for 24 h.</p>
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<p>eIF4A1 overexpression in CLL cells and its regulation of IkBα expression. (<b>A</b>) eIF4A1 protein expression in B-CLL cells from CLL patients (n = 4) compared to that in B cells isolated from a healthy donor. Densitometric quantification of western blot bands is represented relative to the housekeeping gene GAPDH. (<b>B</b>) Western blot analysis of whole cell protein extracts obtained from PBMCs of three CLL patients and B lymphocytes isolated from a healthy donor treated ex vivo with 50 nM Rohinitib for 16 h. (<b>C</b>) NFKBIA mRNA expression levels in samples from five CLL patients treated for 16 h with 250 nM MLN4924 or 50 nM Rohinitib analyzed by NGS. (MLN4924 <span class="html-italic">p</span> = 0.334, rohinitib <span class="html-italic">p</span> = 0.000002). *** <span class="html-italic">p</span> &lt; 0.001. (<b>D</b>) RNA immunoprecipitation assay showing the fold change binding variation of eIF4A1 to NFKBIA mRNA in CLL relative to healthy PBMCs. Measurements were done in triplicate.</p>
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<p>B-CLL cells do not activate NF-kB target genes in response to CHIR-99021. RT-qPCR analysis of the indicated mRNAs in peripheral blood mononuclear cells (PBMCs) from CLL patients (n = 3) or pools of healthy donors (n = 2) as well as in isolated healthy B cells from buffy coats (n = 3), treated ex vivo with 250 nM MLN4924, 1 µM CHIR-99021 or a combination of both for 24 h. The mean of the fold variations and the corresponding standard deviations are represented. Some histograms were cropped to maintain the scale for comparison purposes.</p>
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<p>Combinational induction of B-CLL cell death by CHIR-99021 and MLN4924. (<b>A</b>) Patient B-CLL (n = 11) cell death analysis after the combinational treatment with the GSK-3ß inhibitor CHIR-99021 (1 µM), and the NAE inhibitor MLN4924 (250 nM) measured after 24 h as 7-AAD stained cells by flow cytometry. Response of B-CLL cells from patients (n = 10) to 10 µM Ibrutinib, a standard-of-care therapy, under the same conditions is shown for comparison. Groups were compared to DMSO-treated using Student’s <span class="html-italic">t</span>-test. ** <span class="html-italic">p</span> &lt; 0.01, Student’s <span class="html-italic">t</span>-test. (<b>B</b>) Cell death induction of the combined treatment with 1 µM CHIR-99021 and 250 nM MLN4924 for 24 h over CD19-positive peripheral blood cells obtained from two different pools of healthy donors, measured as 7-AAD-stained cells. (<b>C</b>) Cell viability of B-CLL cells in response to increasing doses of CHIR-99021 and MLN4924 was determined by an XTT assay. The results were analyzed for the synergy score at the SynergyFinder+ web page (<a href="https://synergyfinder.org" target="_blank">https://synergyfinder.org</a>). Representative results of 3 different assays are shown.</p>
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<p>Apoptosis-related gene expression variations in response to MLN4924 and CHIR-99021 in B-CLL cells. A transcriptome analysis was conducted in PBMCs from five CLL patients to identify genes that could be mediating the enhanced cell death induced by the combination of CHIR-99021 (1 µM) and MLN4924 (250 nM). Volcano plots of the mean variations in apoptosis-related genes after 24 h, compared to vehicle treated cells (log2 fold change) obtained with each ex vivo treatment are depicted.</p>
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<p>MLN4924 collaborates with CHIR-99021 in the repression of <span class="html-italic">BCL2</span> and <span class="html-italic">BIRC3</span>. (<b>A</b>) Analysis of the inhibitory effect of either CHIR-99021, at 0.1 and 1 µM (n = 2), or MLN4924 at 250 nM (n = 4) over <span class="html-italic">BCL2</span> mRNA expression in B-CLL cells by RT-qPCR. (<b>B</b>) RT-qPCR analysis of BCL2 and <span class="html-italic">BIRC3</span> messenger RNA expression in B cells from CLL patients (n = 7 and n = 3, respectively) treated ex vivo with 250 nM MLN4924, 1 µM CHIR-99021, or a combination of both for 24 h, relativized to ß-actin mRNA expression. Expression levels in isolated B lymphocytes from three distinct healthy donors or PBMCs from three pools of healthy donors are presented at the same scale for comparative purposes. (<b>C</b>) Densitometric analysis of three western blots demonstrating the impact of 250 nM MLN4924 and/or 1 µM CHIR-99021 on the accumulation of BCL-2 protein in B-CLL cells from three CLL patients. (<b>D</b>) Analysis of the induction of cell death by ABT-199/Venetoclax at 1 nm in combination or not with 1 µM CHIR-99021 and 250 nM MLN4924. Cell death was assessed by 7-AAD staining and subsequent flow cytometry analysis. Groups were compared to DMSO-treated cells using Student’s <span class="html-italic">t</span>-test in all experiments. ** <span class="html-italic">p</span> &lt; 0.01, Student’s <span class="html-italic">t</span>-test.</p>
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16 pages, 1881 KiB  
Article
Ketone Bodies Are Potential Prognostic Biomarkers in Relapsed/Refractory Diffuse Large B-Cell Lymphoma: Results from the R2-GDP-GOTEL Trial
by Sara Fernández-Castillejo, Joan Badia, Luís de la Cruz-Merino, Alejandro Martín Garcia-Sáncho, Fernando Carnicero-González, Natalia Palazón-Carrión, Eduardo Ríos-Herranz, Fátima de la Cruz-Vicente, Antonio Rueda-Domínguez, Natividad Martínez-Banaclocha, José Gómez-Codina, Jorge Labrador, Francisca Martínez-Madueño, Núria Amigó, Antonio Salar-Silvestre, Delvys Rodríguez-Abreu, Laura Gálvez-Carvajal, Margarita Sánchez-Beato, Mariano Provencio-Pulla, Maria Guirado-Risueño, Esteban Nogales, Víctor Sánchez-Margalet, Carlos Jiménez-Cortegana, Guillermo Rodríguez-García, Raquel Cumeras and Josep Gumàadd Show full author list remove Hide full author list
Cancers 2025, 17(3), 532; https://doi.org/10.3390/cancers17030532 - 5 Feb 2025
Viewed by 597
Abstract
Background: Patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who are ineligible for high-dose chemotherapy have limited treatment options and poor life expectancy. The purpose of this study is to identify a serum metabolomic profile that may be predictive of [...] Read more.
Background: Patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who are ineligible for high-dose chemotherapy have limited treatment options and poor life expectancy. The purpose of this study is to identify a serum metabolomic profile that may be predictive of outcome in patients with R/R-DLBCL. Methods: This study included 69 R/R DLBCL patients from the R2-GDP-GOTEL trial (EudraCT 2014-001620-299). Serum samples were collected at baseline, and the mean length of follow-up was 41 months. Serum metabolites were analyzed by nuclear magnetic resonance (NMR). Metabolites were correlated with treatment response, progression-free survival (PFS), and overall survival (OS). Results: Serum levels of 3-hydroxybutyrate (3OHB) and acetone were significantly (p < 0.001) associated with PFS (3OHB: hazard ratio [HR] 7.7, 95% confidence interval [CI] 2.5–24.1; acetone: HR 9.32, 95% CI 2.75–31.6) and OS (3OHB: HR 9.32, 95% CI 2.75–31.6; acetone: HR 1.92, 95% CI 1.36–2.69). Serum values of 141 µM for 3OHB and 40 µM for acetone were the optimal cutoffs associated with the survival outcomes. Elevated 3OHB levels (>141 μM) were specific to the ABC subtype of DLBCL, while acetone levels were elevated in both types of DLCBL but more pronounced in ABC cases. In a multivariate survival analysis, including the International Prognostic Index (IPI) score and refractoriness status (R/R), 3OHB and acetone remained significant. To aid oncologists employing the R2-GDP regime, we constructed PFS and OS nomograms for R/R-DLBCL risk stratification, incorporating 3OHB levels or acetone levels, IPI score, and refractoriness status. The nomogram with 3OHB and refractoriness status showed a time-dependent AUC of 0.86 for 6-month PFS and 0.84 for 12-month OS. These nomograms provide a comprehensive tool for individualized risk assessment and treatment optimization. Conclusions: The ketone bodies 3OHB and acetone are potential prognostic biomarkers of poor outcome in R/R DLBCL patients treated with the R2-GDP regimen, independently of IPI score and chemorefractoriness status. Full article
(This article belongs to the Section Cancer Biomarkers)
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<p>3-Hydroxybutyrate and acetone as prognostic metabolites in the Cox univariate analysis (<b>A</b>,<b>B</b>) and multivariate regressions models (<b>C</b>–<b>F</b>) for progression-free survival (PFS) (<b>A</b>,<b>C</b>,<b>E</b>) and overall survival (OS) (<b>B</b>,<b>D</b>,<b>F</b>).</p>
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<p>Kaplan–Meier survival curves. (<b>A</b>,<b>B</b>), progression-free survival (PFS) and overall survival (OS) for the cutoff of 3-hydroxybutyrate (3OHB); (<b>C</b>,<b>D</b>) PFS and OS for the cutoff of acetone.</p>
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<p>Nomograms for R/R DLBCL risk stratification based on single metabolites and their respective time-dependent ROCs. (<b>A</b>,<b>B</b>) 3-Hydroxybutyrate (3OHB) nomogram for progression-free survival (PFS) and its ROC; (<b>C</b>,<b>D</b>) 3OHB nomogram for overall survival (OS) and its ROC; (<b>E</b>,<b>F</b>) acetone nomogram for PFS and its ROC; (<b>G</b>,<b>H</b>) acetone nomogram for OS and its ROC.</p>
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<p>Ketone bodies of a poor prognosis per cell-of-origin (CoO) subtypes: germinal center B-cell-like (GBC) and activated B-cell-like (ABC) lymphomas. (<b>A</b>) 3-Hydroxybutyrate (3OHB) boxplot per concentration cutoff values (141 μM) and CoO. (<b>B</b>) Acetone boxplot per concentration cutoff values (40 μM) and CoO.</p>
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18 pages, 3540 KiB  
Article
A Retrospective Analysis of the First Clinical 5DCT Workflow
by Michael Lauria, Minji Kim, Dylan O’Connell, Yi Lao, Claudia R. Miller, Louise Naumann, Peter Boyle, Ann Raldow, Alan Lee, Ricky R. Savjani, Drew Moghanaki and Daniel A. Low
Cancers 2025, 17(3), 531; https://doi.org/10.3390/cancers17030531 - 5 Feb 2025
Viewed by 482
Abstract
Background/Objectives: 5DCT was first proposed in 2005 as a motion-compensated CT simulation approach for radiotherapy treatment planning to avoid sorting artifacts that arise in 4DCT when patients breathe irregularly. Since March 2019, 5DCT has been clinically implemented for routine use at our institution [...] Read more.
Background/Objectives: 5DCT was first proposed in 2005 as a motion-compensated CT simulation approach for radiotherapy treatment planning to avoid sorting artifacts that arise in 4DCT when patients breathe irregularly. Since March 2019, 5DCT has been clinically implemented for routine use at our institution to leverage this technological advantage. The clinical workflow includes a quality assurance report that describes the output of primary workflow steps. This study reports on the challenges and quality of the clinical 5DCT workflow using these quality assurance reports. Methods: We evaluated all thoracic 5DCT simulation datasets consecutively acquired at our institution between March 2019 and December 2022 for thoracic radiotherapy treatment planning. The 5DCT datasets utilized motion models constructed from 25 fast-helical free-breathing computed tomography (FHFBCTs) with simultaneous respiratory bellows signal monitoring to reconstruct individual, user-specified breathing-phase images (termed 5DCT phase images) for internal target volume contouring. Each 5DCT dataset was accompanied by a structured quality assurance report composed of qualitative and quantitative measures of the breathing pattern, image quality, DIR quality, model fitting accuracy, and a validation process by which the original FHFBCT scans were regenerated with the 5DCT model. Measures of breathing irregularity, image quality, and DIR quality were retrospectively categorized on a grading scale from 1 (regular breathing and accurate registration/modeling) to 4 (irregular breathing and inaccurate registration/modeling). The validation process was graded according to the same scale, and this grade was termed the suitability-for-treatment-planning (STP) grade. We correlated the graded variables to the STP grade. In addition to the quality assurance reports, we reviewed the contour sessions to determine how often 5DCT phase images were used for treatment planning and delivery. Results: There were 169 5DCT simulation datasets available from 156 patients for analysis. The STP was moderately correlated with breathing irregularity, image quality, and DIR quality (Spearman coefficients: 0.26, 0.30, and 0.50, respectively). Multiple linear regression analysis demonstrated that STP was correlated with regular breathing patterns (p = 0.008), image quality (p < 0.001), and better DIR quality (p < 0.001). 5DCT datasets were used for treatment planning in 82% of cases, while in 12% of cases, a backup image process was used. In total, 6% of image datasets were not used for treatment planning due to factors unrelated to the 5DCT workflow quality. Conclusions: The strongest association with STP was with DIR quality grades, as indicated by both Spearman and multiple linear regression analysis, implying that improvements to DIR accuracy and evaluation may be the best route for further improvement to 5DCT. The high rate of 5DCT phase image use for treatment planning showed that the workflow was reliable, and this has encouraged us to continue to develop and improve the workflow steps. Full article
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<p>5DCT development and implementation timeline.</p>
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<p>5DCT acquisition and reconstruction flowchart. Note that while the registration figure shows lungs, the registration and subsequent DVFs are acquired throughout the entire CT scan.</p>
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<p>Example respiratory trace and subsequent representative breath for one patient, including (<b>a</b>) the respiratory trace annotated with the 5th, 85th, and 95th percentile amplitudes; (<b>b</b>) the representative breath resulting from this breathing trace; (<b>c</b>) the breathing amplitude histogram showing the percent of time spent in each amplitude bin; and (<b>d</b>) the representative breath in the context of the entire breathing trace.</p>
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<p>Flowchart of study design. MIM (MIM Software, Inc., Cleveland, OH, USA) was our RT-PACS system used for contouring.</p>
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<p>Examples of graded variables.</p>
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<p>Pie-chart distribution of STP grade for all 5DCT image acquisitions (n = 169). Grades were assigned to indicate the alignment of the FHFBCTs and the model-generated FHFBCT according to whether they were “very good” (grade 1), “good” (grade 2), “poor” (grade 3), or “very poor” (grade 4). (STP: suitability for treatment planning; FHFBCT: fast-helical free-breathing computed tomography).</p>
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<p>Histogram of grades for FHFBCT quality, DIR quality, and breathing irregularity across all cases.</p>
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<p>Heatmaps showing the coincidental frequency of (<b>a</b>) FHFBCT quality grade, (<b>b</b>) DIR quality grade, and (<b>c</b>) breathing irregularity grade with STP grades for all patients. The colors reflect the numbers displayed and are intended for assisted visual interpretation.</p>
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<p>Pie chart summarizing the proportion of the 5DCT clinical usability categories identified.</p>
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23 pages, 4100 KiB  
Article
Ferroptosis-Related Gene Signatures: Prognostic Role in HPV-Positive Oropharyngeal Squamous Cell Carcinoma
by Deborah Lenoci, Mara Serena Serafini, Marta Lucchetta, Stefano Cavalieri, Ruud H. Brakenhoff, Frank Hoebers, Kathrin Scheckenbach, Tito Poli, Lisa Licitra and Loris De Cecco
Cancers 2025, 17(3), 530; https://doi.org/10.3390/cancers17030530 - 5 Feb 2025
Viewed by 588
Abstract
Background: Despite advances in the management of head and neck squamous cell carcinoma (HNSCC), prognostic models and treatment strategies remain inadequate, particularly for HPV-positive oropharyngeal squamous cell carcinoma (OPSCC). The rising incidence of HPV-positive OPSCC highlights an urgent need for innovative therapeutic approaches. [...] Read more.
Background: Despite advances in the management of head and neck squamous cell carcinoma (HNSCC), prognostic models and treatment strategies remain inadequate, particularly for HPV-positive oropharyngeal squamous cell carcinoma (OPSCC). The rising incidence of HPV-positive OPSCC highlights an urgent need for innovative therapeutic approaches. Ferroptosis, a regulated form of non-apoptotic cell death, has gained attention for its role in cancer progression, but its potential as a prognostic and therapeutic target in HPV-positive OPSCC remains largely unexplored. This study investigates the role of ferroptosis in HPV-positive OPSCC, aiming to identify prognostic markers and provide insights into potential therapeutic strategies that could improve patient outcomes. Methods: Thirteen ferroptosis gene expression signatures were retrieved from the literature, and their performance and association to the immune microenvironment were validated on a meta-analysis of 267 HPV-positive cases (Metanalysis-HPV267) and 286 samples from the BD2Decide project (BD2-HPV286). Results: Our analysis revealed that specific ferroptosis-related gene expression signatures, particularly FER3, FER4, FER6, and FER12, are significantly associated (p-value < 0.05) with high-risk patient groups and adverse tumor microenvironment features, including suppressed immune activity and enhanced stromal involvement. Elevated expression of CAV1, a ferroptosis suppressor, further delineates high-risk profiles. Conclusions: These findings highlight the prognostic significance of ferroptosis in stratifying patients and identifying those with poorer clinical outcomes. Targeting ferroptosis pathways represents a novel and promising approach to addressing the unmet need for effective prognostic and therapeutic strategies in HPV-positive OPSCC. Future research should focus on translating these findings into clinical applications to advance precision oncology and improve outcomes for this growing patient population. Full article
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<p>Consort diagram. Selection of HPV-positive HNSCC dataset.</p>
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<p>Forest plot of Cox regression analysis for the 13 selected ferroptosis signatures in the Metanalysis-HPV267 dataset. Patients were associated with OS as a clinical endpoint with each signature as a continuous trait. A significant HR &gt; 0 was found for FER1, FER3, FER4, FER6, FER8, FER11, and FER12. Data are reported as log2(HR) and 95% confidence intervals.</p>
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<p>Forest plot of Cox regression analysis for the 13 selected ferroptosis signatures in the BD2-HPV286 dataset. A significant HR &gt; 0 was found for FER3, FER4, FER5, FER6, and FER12. Patients were associated with OS as a clinical endpoint with each signature as a continuous trait. Data are reported as log2(HR) and 95% confidence intervals.</p>
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<p>Comparison of the ferroptosis signatures with significant scores on the high-risk cluster (Cl2) in both the Metanalysis-HPV267 and BD2-HPV286 datasets. The tested signatures show significantly higher scores associated with Cl2 (high risk) compared to Cl1 (low risk) and Cl3 (intermediate risk). (<b>A</b>) Correlation of FER3 and prognostic clusters in BD2-HPV286 and Metanalysis-HPV267. (<b>B</b>) Correlation of FER6 and prognostic clusters in BD2-HPV286 and Metanalysis-HPV267. (<b>C</b>) Correlation of FER12 and prognostic clusters in BD2-HPV286 and Metanalysis-HPV267.</p>
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<p>Ferroptosis signatures with significant scores on the high-risk cluster (Cl2) only in one dataset. The tested signatures show significantly higher scores associated with Cl2 (high risk) compared to Cl1 (low risk) and Cl3 (intermediate risk) (<b>A</b>) FER11 in the Metanalysis-HPV267 dataset. (<b>B</b>) FER4 in the BD2-HPV286 dataset.</p>
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<p>Overlap of the genes in the selected signatures. The bars on the bottom left represent the number of genes in each signature. The bars on the plot represent the number of genes in common between the signatures marked with black points on the panel below.</p>
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<p>Expression levels of TRIB3 (<b>A</b>) and CAV1 (<b>B</b>) associated with prognostic clusters in the Metanalysis-HPV267 and BD2-HPV286. No significant association was found for TRIB3, while CAV1 is upregulated in Cl2 compared to Cl1 and Cl3.</p>
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<p>Correlation plot between the selected ferroptosis signatures and the immune, microenvironment, and stroma scores in the Metanalysis-HPV267 cohort. A negative correlation was found between immune score and ferroptosis signatures. The plot depicts the level of correlation by dot size. The bar shows the correlation ranging from 1 to −1 as a color scale.</p>
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<p>Correlation plot between the selected ferroptosis signatures and the immune, microenvironment, and stroma scores in the BD2-HPV286 cohort. A negative correlation was found between immune score and ferroptosis signatures. The plot depicts the level of correlation by dot size. The bar shows the correlation ranging from 1 to −1 as a color scale.</p>
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<p>Predicted sensitivity correlation with ferroptosis signatures. IC50 correlations were predicted in the Metanalysis-HPV267 (<b>A</b>) and BD2-HPV286 (<b>B</b>) datasets. The analysis focused exclusively on targeted and chemotherapeutic compounds approved for clinical use in oncology, excluding experimental drugs. Twelve compounds that exhibited significant negative correlations in both datasets, based on at least one of the selected ferroptosis signatures (i.e., FER3, FER6, FER11, and FER12 for Metanalysis-HPV267; FER3, FER4, FER6, and FER12 for BD2-HPV286), were identified and visualized. The correlation values are reported in <a href="#app1-cancers-17-00530" class="html-app">Tables S5 and S6</a> for Matanalysis-HPV267 and BD2-HPV286, respectively. The size of the circles represents the <span class="html-italic">p</span>-value, while the color indicates the correlation level. Not significant associations (<span class="html-italic">p</span>-value &gt; 0.05) are referred to as X.</p>
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